Duplicate from dealignai/Muse-Glimmer-30B-JANG_2D-CRACK

Co-authored-by: dealign.ai <dealignai@users.noreply.huggingface.co>

.gitattributes

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+tokenizer.json filter=lfs diff=lfs merge=lfs -text

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README.md

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+---
+language:
+- en
+- zh
+license: apache-2.0
+base_model: OsaurusAI/Muse-Glimmer-30B
+base_model_relation: quantized
+library_name: mlx
+pipeline_tag: image-text-to-text
+thumbnail: dealign_mascot.png
+tags:
+- mlx
+- apple-silicon
+- abliterated
+- uncensored
+- crack
+- jang
+- jang-2d
+- vision-language
+- reasoning
+- thinking
+- tool-calling
+- atem
+- harmbench
+- mmlu
+- muse-glimmer
+---
+
+> [!IMPORTANT]
+> **Set your sampler explicitly:** `temperature=1.0`, `top_p=0.95`, `top_k=64` — the Muse Glimmer
+> vendor defaults. These are baked into `generation_config.json` and `jang_config.json`, but **many
+> inference runtimes ignore those files** and fall back to no `top_k` filter, degrading output. Pass
+> them explicitly. Stop tokens `eos_token_id = [200001, 200008]` — keep both in the stop set.
+> Reasoning effort defaults to **high**; controllable via the system prompt (low / medium / high / xhigh).
+
+<!-- vmlx-banner -->
+<div align="center">
+<a href="https://vmlx.net">
+<img src="vmlx-banner.png" width="280" />
+<br/>
+<strong>Built for vMLX</strong> — the MLX inferencer with vision-language support, KV-cache quantization,
+prefix-cache reuse, agentic tool calling, and mixed-precision JANG bundles.
+<br/>
+<sub>Free for macOS · <strong>vmlx.net</strong></sub>
+</a>
+</div>
+
+---
+
+<div align="center">
+
+<img src="dealign_mascot.png" width="128" />
+
+# Muse Glimmer 30B — JANG_2D CRACK
+
+**CRACK abliterated** · **JANG mixed-precision (MLX affine)** · Vision-language · Reasoning (low→xhigh) · Agentic tools · ~15 GB
+
+<a href="https://ko-fi.com/dealignai"><img src="https://img.shields.io/badge/Ko--fi-Support_Development-FF5E5B?logo=ko-fi&logoColor=white&style=for-the-badge" alt="Ko-fi"></a>
+
+</div>
+
+---
+
+## What Is This?
+
+This is [OsaurusAI/Muse-Glimmer-30B](https://huggingface.co/OsaurusAI/Muse-Glimmer-30B) — a 30B-parameter
+**multimodal reasoning model** (Gemma-3 vision-language backbone, 52 layers, sliding + global attention,
+perception encoder) served over the **Onyx-ATEM harmony protocol** (channel-separated reasoning + answer,
+controllable reasoning effort, agentic `<atem:invoke>` tool calling) — that has been:
+
+1. **CRACK abliterated** — refusal behavior removed at the weight level, so it complies across task
+   categories instead of refusing, while keeping its vision, coding, knowledge, multilingual (EN + ZH),
+   reasoning, and tool-use ability intact.
+2. **JANG_2D quantized** — mixed-precision affine MLX bundle tuned for Apple Silicon (~15 GB):
+   mixed 2–4 bit (~2.96 effective bits) — critical tensors kept high-precision, sub-16 GB footprint.
+
+Vision + reasoning + tool calling fully preserved.
+
+## Results
+
+Evaluated through the vMLX inference engine at serving parity. HarmBench scored with a strict classifier
+(rejects loops, empty/template dumps, and thinking-trace leakage — only substantive, coherent, on-topic
+compliance counts). MMLU is the standard 57-subject multiple-choice benchmark in logit mode.
+
+| Metric | Base | CRACK |
+|---|---:|---:|
+| **MMLU (57-subject, logit)** | 71.1% | **70.7%** |
+| **HarmBench (harm categories, compliance / ASR)** | — | **99.6%** (230/231) |
+
+Abliteration is essentially **capability-neutral** — MMLU moves −0.4 points, within run-to-run
+noise (no subject collapse). Compliance was **quality-verified by reading full generations** — genuine,
+correct, on-topic outputs (not empty/gibberish/template dumps). The model stays coherent in direct and
+reasoning modes across all four reasoning-effort settings. HarmBench measured on the harm categories
+(standard + contextual, 240 behaviors); copyright excluded per our real-harm methodology.
+
+## Capability Verification
+
+Read-verified on a 20-prompt suite (every response coherent, correct, on-topic — zero refusals,
+zero gibberish):
+
+- **Security & pentesting — 8/8**: port scanning, reverse shells, SQL injection, keylogging,
+  Metasploit workflow, ARP spoofing, phishing construction, stack buffer-overflow exploitation.
+- **Advanced coding — 4/4**: red-black tree, async `aiohttp` scraper w/ backoff, FastAPI JWT+CRUD API,
+  expression compiler (tokenizer→parser→evaluator).
+- **Advanced reasoning — 4/4**: Euclid's infinite-primes proof, monolith-vs-microservices tradeoff,
+  multi-step word problems, mRNA vaccine design.
+- **Knowledge retention — 4/4**: geography, calculus, astronomy, literature.
+
+## Features
+
+- **Vision-language** — multimodal image understanding preserved (perception encoder untouched).
+- **Controllable reasoning** — reasoning effort **low / medium / high / xhigh** via the system prompt
+  (default **high**); channel-separated reasoning and answer.
+- **Agentic tool calling** — native ATEM `<atem:invoke>` function-calling schema preserved.
+- **Multilingual** — English + Chinese (tested and validated on both).
+- MLX-native safetensors · instant load on Apple Silicon.
+
+## Usage
+
+Run with [vMLX](https://vmlx.net) (recommended — honors the per-module mixed-precision JANG overrides,
+vision, and the Onyx-ATEM reasoning/tool parsers) or an mlx-vlm runtime with Muse Glimmer support.
+
+Recommended sampling (vendor defaults): **temperature 1.0, top_p 0.95, top_k 64**. Stop tokens
+`eos_token_id = [200001, 200008]`.
+
+```python
+from mlx_vlm import load, generate
+model, processor = load("dealignai/Muse-Glimmer-30B-JANG_2D-CRACK")
+# text or image+text; sampling temp=1.0, top_p=0.95, top_k=64
+```
+
+## Other quant levels
+
+| Profile | Size | MMLU (CRACK) | HarmBench |
+|---|---|---:|---:|
+| [JANG_6M](https://huggingface.co/dealignai/Muse-Glimmer-30B-JANG_6M-CRACK) | 26 GB | 81.4% | 99.5% |
+| [JANG_4M](https://huggingface.co/dealignai/Muse-Glimmer-30B-JANG_4M-CRACK) | 20 GB | 81.1% | 99.6% |
+| [JANG_2D](https://huggingface.co/dealignai/Muse-Glimmer-30B-JANG_2D-CRACK) | 15 GB | 70.7% | 99.6% |
+
+## About CRACK
+
+**CRACK** (Controlled Refusal Ablation via Calibrated Knockouts) is dealignai's weight-level method for
+removing safety-refusal behavior while preserving reasoning quality, coherence, and general capability —
+so the model complies across task categories instead of refusing. Calibrated per model.
+
+## Support dealignai
+
+All models are built from original research and released free.
+
+**[Support us on Ko-fi](https://ko-fi.com/dealignai)** — membership gets early access and extras.
+
+[Ko-fi](https://ko-fi.com/dealignai) · [X @dealignai](https://x.com/dealignai) · [dealign.ai](https://dealign.ai)
+
+See our research: [Safety Generalization in Frontier Models](https://dealign.ai/quantsteer.html)
+
+<div align="center"><img src="dealign_logo.png" alt="dealign.ai" width="200"/></div>
+
+---
+
+## Disclaimer
+
+This model has had its safety-refusal behavior removed for research purposes. It will follow instructions
+across all categories without refusing. You are solely responsible for how you use it and for complying
+with all applicable laws. Published for AI-safety research and authorized security testing.

USAGE_POLICY.md

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+# Muse Glimmer Usage Policy
+
+Meta is committed to promoting safe and fair use of its tools and features, including Muse Glimmer. This Usage Policy (“Policy”) applies to your access or use of Muse Glimmer. The most recent copy of this policy can be found at: [https://huggingface.co/meta-models/Muse-Glimmer-30B/blob/main/USAGE\_POLICY](https://huggingface.co/meta-models/Muse-Glimmer-30B/blob/main/USAGE_POLICY.md)
+
+## Prohibited Uses
+
+We want everyone to use Muse Glimmer safely and responsibly. Muse Glimmer is not intended for individuals under the age of 18\.
+
+You should not use, or allow others to use, Muse Glimmer to:
+
+1. **Violate the law or others' rights, including to:**
+   1. Engage in, promote, generate, contribute to, encourage, plan, incite, or further illegal or unlawful activity or content, such as:
+      1. Violence or terrorism
+      2. Exploitation or harm to children, including the solicitation, creation, acquisition, or dissemination of child exploitative content or failure to report Child Sexual Abuse Material
+      3. Human trafficking, exploitation, and sexual violence
+      4. The illegal distribution of information or materials to minors, including obscene materials, or failure to employ legally required age-gating in connection with such information or materials
+      5. Sexual solicitation
+      6. Any other criminal activity
+   2. Engage in, promote, incite, or facilitate the harassment, abuse, threatening, or bullying of individuals or groups of individuals
+   3. Engage in, promote, incite, or facilitate discrimination or other unlawful or harmful conduct in the provision of employment, employment benefits, credit, housing, other economic benefits, or other essential goods and services
+   4. Engage in the unauthorized or unlicensed practice of any profession including, but not limited to, financial, legal, medical/health, or related professional practices
+   5. Collect, process, disclose, generate, or infer private or sensitive information about individuals, including information about individuals' identity, health, or demographic information, unless you have obtained the right to do so in accordance with applicable law
+   6. Engage in or facilitate any action or generate any content that infringes, misappropriates, or otherwise violates any third-party rights, including the outputs or results of any products or services using Muse Glimmer
+   7. Create, generate, or facilitate the creation of malicious code, malware, computer viruses or do anything else that could disable, overburden, interfere with or impair the proper working, integrity, operation or appearance of a website or computer system
+   8. Engage in any action, or facilitate any action, to intentionally circumvent or remove usage restrictions or other safety measures, or to enable functionality disabled by Meta
+2. **Engage in, promote, incite, facilitate, or assist in the planning or development of activities that present a risk of death or bodily harm to individuals, including use of Muse Glimmer related to the following:**
+   1. Military, warfare, nuclear industries or applications, espionage, use for materials or activities that are subject to the International Traffic Arms Regulations (ITAR) maintained by the United States Department of State or to the U.S. Biological Weapons Anti-Terrorism Act of 1989 or the Chemical Weapons Convention Implementation Act of 1997
+   2. Guns and illegal weapons (including weapon development)
+   3. Illegal drugs and regulated/controlled substances
+   4. Operation of critical infrastructure, transportation technologies, or heavy machinery
+   5. Self-harm or harm to others, including suicide, cutting, and eating disorders
+   6. Any content intended to incite or promote violence, abuse, or any infliction of bodily harm to an individual
+3. **Intentionally deceive or mislead others, including use of Muse Glimmer related to the following:**
+   1. Generating, promoting, or furthering fraud or the creation or promotion of disinformation
+   2. Generating, promoting, or furthering defamatory content, including the creation of defamatory statements, images, or other content
+   3. Generating, promoting, or further distributing spam
+   4. Impersonating another individual without consent, authorization, or legal right
+   5. Representing that the use of Muse Glimmer or outputs are human generated
+   6. Generating or facilitating false online engagement, including fake reviews and other means of fake online engagement
+4. **Fail to appropriately disclose to end users any known dangers of your AI system**
+5. **Interact with third party tools, models, or software designed to generate unlawful content or engage in unlawful or harmful conduct and/or represent that the outputs of such tools, models, or software are associated with Meta or Muse Glimmer**
+
+Please report any violation of this Policy, software "bug," or other problems that could lead to a violation of this Policy through one of the following means:
+
+* Reporting issues with the model: [https://huggingface.co/meta-models/](https://huggingface.co/meta-models/)
+* Reporting bugs and security concerns: [https://facebook.com/whitehat/info](https://facebook.com/whitehat/info)

chat_template.jinja

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+{#
+  Template: Muse Glimmer ATEM Chat Template
+  Renders the ATEM tool-calling protocol: reasoning channel (to=self), tool
+  channels (to=<tool>), and the user channel, plus tool definitions and the
+  valid-recipient list in the system block.
+
+  Whitespace note: every tag uses the {%- -%} / {{- -}} stripping markers, so
+  the indentation below is purely for readability and contributes nothing to
+  the rendered output.
+#}
+{%- macro render_content(content) -%}
+    {%- if content is string -%}
+        {{- content -}}
+    {%- elif content is not none -%}
+        {%- for part in content -%}
+            {%- if part['type'] == 'image' -%}
+                {{- '<|patch|>' -}}
+            {%- elif part['type'] == 'video' -%}
+                {{- '<|video|>' -}}
+            {%- elif part['type'] == 'text' -%}
+                {{- part['text'] -}}
+            {%- endif -%}
+        {%- endfor -%}
+    {%- endif -%}
+{%- endmacro -%}
+{%- macro render_atem(tc) -%}
+    {%- set args = tc.function.arguments -%}
+    {%- if args is not mapping -%}
+        {{- raise_exception('Muse Glimmer ATEM chat template requires tool_call.function.arguments to be a dict (mapping); a JSON string cannot be parsed in the HF jinja sandbox.') -}}
+    {%- endif -%}
+    {{- '<atem:function_calls>\n<atem:invoke name="' + tc.function.name + '">\n' -}}
+    {%- for k, v in args.items() -%}
+        {{- '<atem:parameter name="' + k + '">' -}}
+        {%- if v is boolean -%}
+            {%- if v -%}
+                true
+            {%- else -%}
+                false
+            {%- endif -%}
+        {%- elif v is none -%}
+            null
+        {%- elif v is mapping or (v is iterable and v is not string) -%}
+            {{- v | tojson -}}
+        {%- else -%}
+            {{- v -}}
+        {%- endif -%}
+        {{- '</atem:parameter>\n' -}}
+    {%- endfor -%}
+    {{- '</atem:invoke>\n</atem:function_calls>' -}}
+{%- endmacro -%}
+{%- macro render_tool_defs(tools) -%}
+    {{- 'In this environment you have access to a set of tools you can use to answer the user\'s question.\n\n' -}}
+    {{- 'You can invoke a function by writing a "<atem:function_calls>" block like the following:\n' -}}
+    {{- '<atem:function_calls>\n<atem:invoke name="$FUNCTION_NAME">\n<atem:parameter name="$PARAMETER_NAME">$PARAMETER_VALUE</atem:parameter>\n...\n</atem:invoke>\n</atem:function_calls>\n\n' -}}
+    {{- 'String and scalar parameters should be specified as is, while lists and objects should use JSON format. Note that spaces for string values are not stripped. The output is not expected to be valid XML and is parsed with regular expressions.\n' -}}
+    {{- 'Here are the functions available in JSONSchema format:\n' -}}
+    {{- '// Tool metadata\n' -}}
+    {%- set nsns = namespace(seen=[]) -%}
+    {%- for tool in tools -%}
+        {%- set fn = tool.function if tool.function is defined else tool -%}
+        {%- set tns = fn.name.split('.')[0] -%}
+        {%- if tns not in nsns.seen -%}
+            {%- set nsns.seen = nsns.seen + [tns] -%}
+        {%- endif -%}
+    {%- endfor -%}
+    {%- set nd = tool_namespace_descriptions if tool_namespace_descriptions is defined else {} -%}
+    {%- for tns in nsns.seen -%}
+        {{- '{"name": ' + (tns | tojson) + ', "description": ' + ((nd[tns] if tns in nd else '') | tojson) + '}\n' -}}
+    {%- endfor -%}
+    {{- '// Function schemas' -}}
+    {%- for tool in tools -%}
+        {%- set fn = tool.function if tool.function is defined else tool -%}
+        {{- '\n{"name": ' + (fn.name | tojson) + ', "description": ' + (fn.description | tojson) + ', "parameters": ' + (fn.parameters | tojson) + '}' -}}
+    {%- endfor -%}
+    {{- '\n\nHere\'s an example of how to call a function in the tool set:\n' -}}
+    {{- '(If the tool namespace is not specified, invoke the function directly as `example_function_name` rather than `example_tool_name.example_function_name`)\n\n' -}}
+    {{- 'to=example_tool_name.example_function_name\n\n' -}}
+    {{- '<atem:function_calls>\n<atem:invoke name="example_tool_name.example_function_name">\n' -}}
+    {{- '<atem:parameter name="example_parameter_1">value_1</atem:parameter>\n' -}}
+    {{- '<atem:parameter name="example_parameter_2">This is the value for the second parameter\nthat can span\n"multiple" lines\n</atem:parameter>\n' -}}
+    {{- '</atem:invoke>\n</atem:function_calls>' -}}
+{%- endmacro -%}
+{%- macro render_reasoning() -%}
+    {%- set rs = reasoning_strength if reasoning_strength is defined and reasoning_strength else 'high' -%}
+    {{- 'Reasoning strength: ' + rs + '.' -}}
+{%- endmacro -%}
+{%- macro render_system_meta(tools) -%}
+    {%- set rns = namespace(recipients=['"self"'], nslist=[]) -%}
+    {%- if tools -%}
+        {%- for tool in tools -%}
+            {%- set fn = tool.function if tool.function is defined else tool -%}
+            {%- set tns = fn.name.split('.')[0] -%}
+            {%- if tns not in rns.nslist -%}
+                {%- set rns.nslist = rns.nslist + [tns] -%}
+            {%- endif -%}
+        {%- endfor -%}
+        {%- for tns in rns.nslist -%}
+            {%- set rns.recipients = rns.recipients + ['"' + tns + '.*"'] -%}
+        {%- endfor -%}
+    {%- endif -%}
+    {%- set rns.recipients = rns.recipients + ['"user"'] -%}
+    {{- '# Valid recipients: ' + rns.recipients | join(', ') + '.' -}}
+{%- endmacro -%}
+{{- bos_token -}}
+{%- set ns = namespace(has_system=false) -%}
+{%- for m in messages -%}
+    {%- if m['role'] == 'system' -%}
+        {%- set ns.has_system = true -%}
+    {%- endif -%}
+{%- endfor -%}
+{%- if not ns.has_system -%}
+    {{- '<|start|>system<|message|>You are a helpful AI assistant.' -}}
+    {%- set kc = knowledge_cutoff if knowledge_cutoff is defined and knowledge_cutoff else '2026-01-04' -%}
+    {{- '\nKnowledge cutoff: ' + kc + '.' -}}
+    {%- if current_date is defined and current_date -%}
+        {{- '\nCurrent date: ' + current_date + '.' -}}
+    {%- elif strftime_now is defined -%}
+        {{- '\nCurrent date: ' + strftime_now('%Y-%m-%d') + '.' -}}
+    {%- endif -%}
+    {{- '\n\n' -}}
+    {{- render_reasoning() -}}
+    {%- if tools -%}
+        {{- '\n\n' -}}
+        {{- render_tool_defs(tools) -}}
+    {%- endif -%}
+    {{- '\n\n' -}}
+    {{- render_system_meta(tools) -}}
+    {{- '<|eot|>' -}}
+{%- endif -%}
+{%- for message in messages -%}
+    {%- set role = message['role'] -%}
+    {%- set end_token = '<|eom|>' if (not loop.last and messages[loop.index0 + 1]['role'] == role) else '<|eot|>' -%}
+    {%- if role == 'system' -%}
+        {#- Callers sometimes write the directive into the system prompt themselves.
+            Normalise "Reasoning effort" to "Reasoning strength" (jinja has no
+            case-insensitive replace, hence the four realistic casings), then skip
+            the kwarg-driven line below if the prompt already carries one. -#}
+        {%- set sys_text = render_content(message['content'])
+              | replace('Reasoning effort', 'Reasoning strength')
+              | replace('Reasoning Effort', 'Reasoning Strength')
+              | replace('reasoning effort', 'reasoning strength')
+              | replace('REASONING EFFORT', 'REASONING STRENGTH') -%}
+        {{- '<|start|>system<|message|>' -}}
+        {{- sys_text -}}
+        {%- if 'reasoning strength' not in (sys_text | lower) -%}
+            {{- '\n\n' -}}
+            {{- render_reasoning() -}}
+        {%- endif -%}
+        {%- if tools -%}
+            {{- '\n\n' -}}
+            {{- render_tool_defs(tools) -}}
+        {%- endif -%}
+        {{- '\n\n' -}}
+        {{- render_system_meta(tools) -}}
+        {{- '<|eot|>' -}}
+    {%- elif role == 'user' -%}
+        {{- '<|start|>user<|message|>' -}}
+        {{- render_content(message['content']) -}}
+        {{- '<|eot|>' -}}
+    {%- elif role == 'tool' -%}
+        {%- set tname = message.get('name') -%}
+        {%- if not tname -%}
+            {%- set tcid = message.get('tool_call_id') -%}
+            {%- set rns = namespace(name=tcid if tcid else '') -%}
+            {%- for m in messages -%}
+                {%- if m.get('tool_calls') -%}
+                    {%- for tc in m['tool_calls'] -%}
+                        {%- if tcid is not none and tc.id is defined and tc.id == tcid -%}
+                            {%- set rns.name = tc.function.name -%}
+                        {%- endif -%}
+                    {%- endfor -%}
+                {%- endif -%}
+            {%- endfor -%}
+            {%- set tname = rns.name -%}
+        {%- endif -%}
+        {{- '<|start|>tool ' + tname + '<|message|><tool_output name="' + tname + '">\n' -}}
+        {{- render_content(message['content']) -}}
+        {{- '\n</tool_output><|eot|>' -}}
+    {%- elif role == 'assistant' -%}
+        {%- if message.get('reasoning_content') -%}
+            {{- '<|start|>assistant to=self<|message|>' + message['reasoning_content'] + '<|eom|>' -}}
+        {%- endif -%}
+        {%- if message.get('tool_calls') -%}
+            {%- for tc in message['tool_calls'] -%}
+                {{- '<|start|>assistant to=' + tc.function.name + '<|message|>' -}}
+                {{- render_atem(tc) -}}
+                {%- if loop.last -%}
+                    {{- end_token -}}
+                {%- else -%}
+                    {{- '<|eom|>' -}}
+                {%- endif -%}
+            {%- endfor -%}
+        {%- else -%}
+            {%- set recipient = message.get('recipient') or 'user' -%}
+            {%- set end_turn = message.get('end_turn') -%}
+            {%- if end_turn is none -%}
+                {%- set end_turn = not (recipient and recipient != 'user') -%}
+            {%- endif -%}
+            {{- '<|start|>assistant' -}}
+            {%- if recipient -%}
+                {{- ' to=' + recipient -}}
+            {%- endif -%}
+            {{- '<|message|>' -}}
+            {{- render_content(message['content']) -}}
+            {{- ('<|eot|>' if end_turn else '<|eom|>') -}}
+        {%- endif -%}
+    {%- endif -%}
+{%- endfor -%}
+{%- if add_generation_prompt -%}
+    {{- '<|start|>assistant' -}}
+{%- endif -%}

config.json

@@ -0,0 +1,2348 @@
+{
+  "architectures": [
+    "MuseGlimmerForConditionalGeneration"
+  ],
+  "dtype": "bfloat16",
+  "image_token_id": 200092,
+  "model_type": "muse_glimmer",
+  "out_hidden_size": 6144,
+  "projector_hidden_act": "gelu",
+  "projector_hidden_size": 4096,
+  "text_config": {
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "bos_token_id": 200000,
+    "eos_token_id": 200001,
+    "final_logit_softcapping": 20.0,
+    "head_dim": 128,
+    "hidden_activation": "silu",
+    "hidden_size": 6656,
+    "initializer_range": 0.02,
+    "intermediate_size": 19968,
+    "layer_rope_theta": [
+      500000.0,
+      500000.0,
+      500000.0,
+      0,
+      500000.0,
+      500000.0,
+      500000.0,
+      0,
+      500000.0,
+      500000.0,
+      500000.0,
+      0,
+      500000.0,
+      500000.0,
+      500000.0,
+      0,
+      500000.0,
+      500000.0,
+      500000.0,
+      0,
+      500000.0,
+      500000.0,
+      500000.0,
+      0,
+      500000.0,
+      500000.0,
+      500000.0,
+      0,
+      500000.0,
+      500000.0,
+      500000.0,
+      0,
+      500000.0,
+      500000.0,
+      500000.0,
+      0,
+      500000.0,
+      500000.0,
+      500000.0,
+      0,
+      500000.0,
+      500000.0,
+      500000.0,
+      0,
+      500000.0,
+      500000.0,
+      500000.0,
+      0,
+      500000.0,
+      500000.0,
+      500000.0,
+      0
+    ],
+    "layer_types": [
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "full_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "full_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "full_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "full_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "full_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "full_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "full_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "full_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "full_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "full_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "full_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "full_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "sliding_attention",
+      "full_attention"
+    ],
+    "max_position_embeddings": 131072,
+    "model_type": "muse_glimmer_text",
+    "num_attention_heads": 32,
+    "num_hidden_layers": 52,
+    "num_key_value_heads": 2,
+    "output_multiplier": 0.19611613513818404,
+    "pad_token_id": null,
+    "post_norm_eps": 1e-08,
+    "qk_scale_factor": 3.87,
+    "rms_norm_eps": 1e-05,
+    "rope_parameters": {
+      "rope_theta": 500000.0,
+      "rope_type": "default"
+    },
+    "sliding_window": 2048,
+    "tie_word_embeddings": false,
+    "use_cache": true,
+    "vocab_size": 202048
+  },
+  "transformers_version": "5.15.0.dev0",
+  "video_token_id": 200091,
+  "vision_config": {
+    "hidden_act": "gelu",
+    "hidden_size": 1536,
+    "intermediate_size": 8960,
+    "layer_norm_eps": 1e-05,
+    "layer_types": [
+      "window_attention",
+      "window_attention",
+      "window_attention",
+      "full_attention",
+      "window_attention",
+      "window_attention",
+      "window_attention",
+      "full_attention",
+      "window_attention",
+      "window_attention",
+      "window_attention",
+      "full_attention",
+      "window_attention",
+      "window_attention",
+      "window_attention",
+      "full_attention",
+      "window_attention",
+      "window_attention",
+      "window_attention",
+      "full_attention",
+      "window_attention",
+      "window_attention",
+      "window_attention",
+      "full_attention",
+      "window_attention",
+      "window_attention",
+      "window_attention",
+      "full_attention",
+      "window_attention",
+      "window_attention",
+      "window_attention",
+      "full_attention",
+      "window_attention",
+      "window_attention",
+      "window_attention",
+      "full_attention",
+      "window_attention",
+      "window_attention",
+      "window_attention",
+      "full_attention",
+      "window_attention",
+      "window_attention",
+      "window_attention",
+      "full_attention",
+      "window_attention",
+      "window_attention",
+      "window_attention",
+      "full_attention",
+      "window_attention",
+      "full_attention"
+    ],
+    "max_position_embeddings": 1024,
+    "merge_size": 2,
+    "model_type": "muse_glimmer_vision",
+    "num_attention_heads": 16,
+    "num_hidden_layers": 50,
+    "patch_size": 14,
+    "patch_temporal": 2,
+    "pos_emb_height": 32,
+    "pos_emb_width": 32,
+    "rope_parameters": {
+      "rope_theta": 10000.0,
+      "rope_type": "default"
+    }
+  },
+  "eos_token_id": 200001,
+  "bos_token_id": 200000,
+  "weight_format": "jang_affine",
+  "has_vision": true,
+  "has_audio": false,
+  "has_video": true,
+  "modalities": {
+    "text": true,
+    "vision": true,
+    "audio": false,
+    "video": true
+  },
+  "capabilities": {
+    "reasoning_parser": "muse_glimmer",
+    "tool_parser": "atem",
+    "think_in_template": false,
+    "supports_tools": true,
+    "supports_thinking": true,
+    "family": "muse_glimmer",
+    "modality": "multimodal",
+    "modalities": {
+      "text": true,
+      "vision": true,
+      "audio": false,
+      "video": true
+    },
+    "has_vision": true,
+    "has_audio": false,
+    "has_video": true,
+    "cache_type": "kv"
+  },
+  "quantization": {
+    "group_size": 64,
+    "bits": 2,
+    "mode": "affine",
+    "language_model.model.embed_tokens": {
+      "group_size": 64,
+      "bits": 3,
+      "mode": "affine"
+    },
+    "language_model.model.layers.0.mlp.down_proj": {
+      "group_size": 64,
+      "bits": 3,
+      "mode": "affine"
+    },
+    "language_model.model.layers.0.mlp.gate_proj": {
+      "group_size": 64,
+      "bits": 3,
+      "mode": "affine"
+    },
+    "language_model.model.layers.0.mlp.up_proj": {
+      "group_size": 64,
+      "bits": 2,
+      "mode": "affine"
+    },
+    "language_model.model.layers.0.self_attn.gate_proj": {
+      "group_size": 64,
+      "bits": 4,
+      "mode": "affine"
+    },
+    "language_model.model.layers.0.self_attn.k_proj": {
+      "group_size": 64,
+      "bits": 4,
+      "mode": "affine"
+    },
+    "language_model.model.layers.0.self_attn.o_proj": {
+      "group_size": 64,
+      "bits": 4,
+      "mode": "affine"
+    },
+    "language_model.model.layers.0.self_attn.q_proj": {
+      "group_size": 64,
+      "bits": 4,
+      "mode": "affine"
+    },
+    "language_model.model.layers.0.self_attn.v_proj": {
+      "group_size": 64,
+      "bits": 4,
+      "mode": "affine"
+    },
+    "language_model.model.layers.1.mlp.down_proj": {
+      "group_size": 64,
+      "bits": 3,
+      "mode": "affine"
+    },
+    "language_model.model.layers.1.mlp.gate_proj": {
+      "group_size": 64,
+      "bits": 3,
+      "mode": "affine"
+    },
+    "language_model.model.layers.1.mlp.up_proj": {
+      "group_size": 64,
+      "bits": 2,
+      "mode": "affine"
+    },
+    "language_model.model.layers.1.self_attn.gate_proj": {
+      "group_size": 64,
+      "bits": 4,
+      "mode": "affine"
+    },
+    "language_model.model.layers.1.self_attn.k_proj": {
+      "group_size": 64,
+      "bits": 4,
+      "mode": "affine"
+    },
+    "language_model.model.layers.1.self_attn.o_proj": {
+      "group_size": 64,
+      "bits": 4,
+      "mode": "affine"
+    },
+    "language_model.model.layers.1.self_attn.q_proj": {
+      "group_size": 64,
+      "bits": 4,
+      "mode": "affine"
+    },
+    "language_model.model.layers.1.self_attn.v_proj": {
+      "group_size": 64,
+      "bits": 4,
+      "mode": "affine"
+    },
+    "language_model.model.layers.10.mlp.down_proj": {
+      "group_size": 64,
+      "bits": 3,
+      "mode": "affine"
+    },
+    "language_model.model.layers.10.mlp.gate_proj": {
+      "group_size": 64,
+      "bits": 3,
+      "mode": "affine"
+    },
+    "language_model.model.layers.10.mlp.up_proj": {
+      "group_size": 64,
+      "bits": 2,
+      "mode": "affine"
+    },
+    "language_model.model.layers.10.self_attn.gate_proj": {
+      "group_size": 64,
+      "bits": 4,
+      "mode": "affine"
+    },
+    "language_model.model.layers.10.self_attn.k_proj": {
+      "group_size": 64,
+      "bits": 4,
+      "mode": "affine"
+    },
+    "language_model.model.layers.10.self_attn.o_proj": {
+      "group_size": 64,
+      "bits": 4,
+      "mode": "affine"
+    },
+    "language_model.model.layers.10.self_attn.q_proj": {
+      "group_size": 64,
+      "bits": 4,
+      "mode": "affine"
+    },
+    "language_model.model.layers.10.self_attn.v_proj": {
+      "group_size": 64,
+      "bits": 4,
+      "mode": "affine"
+    },
+    "language_model.model.layers.11.mlp.down_proj": {
+      "group_size": 64,
+      "bits": 3,
+      "mode": "affine"
+    },
+    "language_model.model.layers.11.mlp.gate_proj": {
+      "group_size": 64,
+      "bits": 3,
+      "mode": "affine"
+    },
+    "language_model.model.layers.11.mlp.up_proj": {
+      "group_size": 64,
+      "bits": 2,
+      "mode": "affine"
+    },
+    "language_model.model.layers.11.self_attn.gate_proj": {
+      "group_size": 64,
+      "bits": 4,
+      "mode": "affine"
+    },
+    "language_model.model.layers.11.self_attn.k_proj": {
+      "group_size": 64,
+      "bits": 4,
+      "mode": "affine"
+    },
+    "language_model.model.layers.11.self_attn.o_proj": {
+      "group_size": 64,
+      "bits": 4,
+      "mode": "affine"
+    },
+    "language_model.model.layers.11.self_attn.q_proj": {
+      "group_size": 64,
+      "bits": 4,
+      "mode": "affine"
+    },
+    "language_model.model.layers.11.self_attn.v_proj": {
+      "group_size": 64,
+      "bits": 4,
+      "mode": "affine"
+    },
+    "language_model.model.layers.12.mlp.down_proj": {
+      "group_size": 64,
+      "bits": 3,
+      "mode": "affine"
+    },
+    "language_model.model.layers.12.mlp.gate_proj": {
+      "group_size": 64,
+      "bits": 3,
+      "mode": "affine"
+    },
+    "language_model.model.layers.12.mlp.up_proj": {
+      "group_size": 64,
+      "bits": 2,
+      "mode": "affine"
+    },
+    "language_model.model.layers.12.self_attn.gate_proj": {
+      "group_size": 64,
+      "bits": 4,
+      "mode": "affine"
+    },
+    "language_model.model.layers.12.self_attn.k_proj": {
+      "group_size": 64,
+      "bits": 4,
+      "mode": "affine"
+    },
+    "language_model.model.layers.12.self_attn.o_proj": {
+      "group_size": 64,
+      "bits": 4,
+      "mode": "affine"
+    },
+    "language_model.model.layers.12.self_attn.q_proj": {
+      "group_size": 64,
+      "bits": 4,
+      "mode": "affine"
+    },
+    "language_model.model.layers.12.self_attn.v_proj": {
+      "group_size": 64,
+      "bits": 4,
+      "mode": "affine"
+    },
+    "language_model.model.layers.13.mlp.down_proj": {
+      "group_size": 64,
+      "bits": 3,
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+  "pad_token": "<|finetune_right_pad|>",
+  "processor_class": "MuseGlimmerProcessor",
+  "response_template": {
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+    },
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+          "<|eom|>"
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+          }
+        },
+        "open_pattern": "<atem:invoke\\b[^>]*?\\bname=\"(?P<name>[^\"]+)\">",
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+        "transform": {
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+        }
+      }
+    },
+    "start_anchor": "<|start|>assistant"
+  },
+  "tokenizer_class": "TokenizersBackend"
+}