Text Generation
PEFT
Safetensors
lora
open-jev
classification
logprob
minicpm
adapters
conversational
Instructions to use nicolasembleton/openjev-minicpm5-2b-lora-phase1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use nicolasembleton/openjev-minicpm5-2b-lora-phase1 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("openbmb/MiniCPM5-2B") model = PeftModel.from_pretrained(base_model, "nicolasembleton/openjev-minicpm5-2b-lora-phase1") - Notebooks
- Google Colab
- Kaggle
Open-Jev Phase-1 MiniCPM5-2B LoRA adapter (test 0.467→0.702)
Browse files- README.md +68 -0
- adapter_config.json +51 -0
- adapter_model.safetensors +3 -0
- chat_template.jinja +177 -0
- tokenizer.json +0 -0
- tokenizer_config.json +17 -0
README.md
ADDED
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@@ -0,0 +1,68 @@
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| 1 |
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---
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| 2 |
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base_model: openbmb/MiniCPM5-2B
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| 3 |
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library_name: peft
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| 4 |
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license: apache-2.0
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| 5 |
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pipeline_tag: text-generation
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| 6 |
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tags:
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| 7 |
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- lora
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| 8 |
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- peft
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| 9 |
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- open-jev
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| 10 |
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- classification
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| 11 |
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- logprob
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| 12 |
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- minicpm
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| 13 |
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- adapters
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datasets:
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- ZefanCai/Open-Jev-v1.1
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---
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# Open-Jev Phase-1 LoRA — MiniCPM5-2B
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| 19 |
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| 20 |
+
PEFT LoRA adapter for [openbmb/MiniCPM5-2B](https://huggingface.co/openbmb/MiniCPM5-2B), fine-tuned for **closed-set first-token scoring** on Open-Jev Choice / Noul / Score fields (Bev/Jev-style: one forward pass, candidate-token logits; not free-form generation).
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| 21 |
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| 22 |
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## Results (frozen panel, never in train)
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| Slice | Metric | Zero-shot | This LoRA | Δ |
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| 25 |
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|-------|--------|-----------|-----------|---|
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| 26 |
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| Test n=900 | overall accuracy | 0.467 | **0.702** | +23.6 pp |
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| 27 |
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| Test | Noul recall | 0.118 | **0.735** | +61.8 pp |
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| OOD n=300 | overall accuracy | 0.473 | **0.710** | +23.7 pp |
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Scorekeeper planted gold; see local `results/openjev-phase1/RUN_CARD.md` for full tables.
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## Recipe
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- **Base:** `openbmb/MiniCPM5-2B`
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- **Train:** stratified Open-Jev subset, n=6000 (2000 Choice / 2000 Noul / 2000 Score); dataset rev `10ad6888333fa97f8c948192797bad3de3040802`
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| 36 |
+
- **Objective:** causal LM loss **only** on the gold index-surrogate token after `Answer: `
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| 37 |
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- **LoRA:** r=16, α=32, dropout=0.05; targets `q/k/v/o/gate/up/down_proj`
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| 38 |
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- **Train:** 1 epoch, lr=2e-4, effective batch 16, max length 2048, bfloat16
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- **Hardware:** Modal A10G (~59.5 min wall, ~15.2 GB peak VRAM)
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- **Seed:** 20260924
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## Load
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|
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```python
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| 45 |
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from transformers import AutoModelForCausalLM, AutoTokenizer
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| 46 |
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from peft import PeftModel
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| 47 |
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|
| 48 |
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base_id = "openbmb/MiniCPM5-2B"
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adapter_id = "nicolasembleton/openjev-minicpm5-2b-lora-phase1"
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| 50 |
+
|
| 51 |
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tok = AutoTokenizer.from_pretrained(base_id, trust_remote_code=True)
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| 52 |
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model = AutoModelForCausalLM.from_pretrained(base_id, trust_remote_code=True, torch_dtype="auto")
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| 53 |
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model = PeftModel.from_pretrained(model, adapter_id)
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| 54 |
+
```
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| 55 |
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| 56 |
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For Open-Jev TypeSafe-compatible scoring, point `OPENJEV_ADAPTER_PATH` at this adapter (or a local checkout) on top of the same base.
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| 57 |
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|
| 58 |
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## Browser / WebGPU note
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| 59 |
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|
| 60 |
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This repo is the **PEFT adapter only**. In-browser Transformers.js needs a **merged** weights export (and ideally quantized ONNX). That path is separate from this Hub upload.
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| 61 |
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| 62 |
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## Intended use
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| 63 |
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| 64 |
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Research and demos of closed-set Choice / Noul / Score scoring on Open-Jev-style prompts. Not a general chat model. Do not treat closed-menu argmax as ground truth without an external scorekeeper.
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| 65 |
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| 66 |
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## License
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| 67 |
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|
| 68 |
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Adapter weights follow the base model license terms for derivatives of MiniCPM5-2B (Apache-2.0 style redistribution where permitted by the base). Training data: Open-Jev v1.1.
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adapter_config.json
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{
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| 2 |
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"alora_invocation_tokens": null,
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| 3 |
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"alpha_pattern": {},
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| 4 |
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"arrow_config": null,
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| 5 |
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"auto_mapping": null,
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| 6 |
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"base_model_name_or_path": "openbmb/MiniCPM5-2B",
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| 7 |
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"bias": "none",
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| 8 |
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"corda_config": null,
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| 9 |
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"ensure_weight_tying": false,
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| 10 |
+
"eva_config": null,
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| 11 |
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"exclude_modules": null,
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| 12 |
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"fan_in_fan_out": false,
|
| 13 |
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"inference_mode": true,
|
| 14 |
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"init_lora_weights": true,
|
| 15 |
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"kasa_config": null,
|
| 16 |
+
"layer_replication": null,
|
| 17 |
+
"layers_pattern": null,
|
| 18 |
+
"layers_to_transform": null,
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| 19 |
+
"loftq_config": {},
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| 20 |
+
"lora_alpha": 32,
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| 21 |
+
"lora_bias": false,
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| 22 |
+
"lora_dropout": 0.05,
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| 23 |
+
"lora_ga_config": null,
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| 24 |
+
"megatron_config": null,
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| 25 |
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"megatron_core": "megatron.core",
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| 26 |
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"modules_to_save": null,
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| 27 |
+
"monteclora_config": null,
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| 28 |
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"peft_type": "LORA",
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| 29 |
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"peft_version": "0.21.0",
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| 30 |
+
"qalora_group_size": 16,
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| 31 |
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"r": 16,
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| 32 |
+
"rank_pattern": {},
|
| 33 |
+
"revision": null,
|
| 34 |
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"target_modules": [
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| 35 |
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"gate_proj",
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| 36 |
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"v_proj",
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| 37 |
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"o_proj",
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| 38 |
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"k_proj",
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| 39 |
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"up_proj",
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| 40 |
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"down_proj",
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| 41 |
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"q_proj"
|
| 42 |
+
],
|
| 43 |
+
"target_parameters": null,
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| 44 |
+
"task_type": "CAUSAL_LM",
|
| 45 |
+
"trainable_token_indices": null,
|
| 46 |
+
"use_bdlora": null,
|
| 47 |
+
"use_dora": false,
|
| 48 |
+
"use_qalora": false,
|
| 49 |
+
"use_rslora": false,
|
| 50 |
+
"velora_config": null
|
| 51 |
+
}
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adapter_model.safetensors
ADDED
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@@ -0,0 +1,3 @@
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version https://git-lfs.github.com/spec/v1
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+
oid sha256:acdf695020a1933ee7dc51b22a2b4fcdeb469f0094e0972097bb8c529e91465e
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| 3 |
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size 100544848
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chat_template.jinja
ADDED
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@@ -0,0 +1,177 @@
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| 1 |
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{{- bos_token }}{%- if tools %}
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| 2 |
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{%- set tool_definitions %}
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| 3 |
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{{- "# Tools\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>" }}
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| 4 |
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{%- for tool in tools %}
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| 5 |
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{{- "\n" }}
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| 6 |
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{{- tool | tojson(ensure_ascii=False) }}
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| 7 |
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{%- endfor %}
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| 8 |
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{{- '\n</tools>\n\nTool usage guidelines:\n- You may call zero or more functions. If no function calls are needed, just answer normally and do not include any <function ... </function>.\n- When calling a function, return an XML object within <function ... </function> using:\n<function name="function-name"><param name="param-name">param-value</param></function>\n- param-value may be multi-line. If it contains <, & or newline characters, wrap it in a CDATA block: <param name="param-name"><![CDATA[...multi-line value...]]></param>' }}
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| 9 |
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{%- endset %}
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| 10 |
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| 11 |
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{{- '<|im_start|>system\n' }}
|
| 12 |
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{%- if messages[0].role == 'system' %}
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| 13 |
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{%- if '<tool_def_sep>' in messages[0].content %}
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| 14 |
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{{- messages[0].content.replace('<tool_def_sep>', tool_definitions) }}
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| 15 |
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{%- else %}
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| 16 |
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{{- messages[0].content + '\n\n' + tool_definitions }}
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| 17 |
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{%- endif %}
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| 18 |
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{%- else %}
|
| 19 |
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{{- tool_definitions.lstrip() }}
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| 20 |
+
{%- endif %}
|
| 21 |
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{{- '<|im_end|>\n' }}
|
| 22 |
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{%- else %}
|
| 23 |
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{%- if messages[0].role == 'system' %}
|
| 24 |
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{{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
|
| 25 |
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{%- endif %}
|
| 26 |
+
{%- endif %}
|
| 27 |
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{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
|
| 28 |
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{%- for message in messages[::-1] %}
|
| 29 |
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{%- set index = (messages|length - 1) - loop.index0 %}
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| 30 |
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{%- if ns.multi_step_tool and message.role == "user" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
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| 31 |
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{%- set ns.multi_step_tool = false %}
|
| 32 |
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{%- set ns.last_query_index = index %}
|
| 33 |
+
{%- endif %}
|
| 34 |
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{%- endfor %}
|
| 35 |
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{%- for message in messages %}
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| 36 |
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{%- if message.content is string %}
|
| 37 |
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{%- set content = message.content %}
|
| 38 |
+
{%- else %}
|
| 39 |
+
{%- set content = '' %}
|
| 40 |
+
{%- endif %}
|
| 41 |
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{%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
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| 42 |
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{{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
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| 43 |
+
{%- elif message.role == "assistant" %}
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| 44 |
+
{%- set reasoning_content = '' %}
|
| 45 |
+
{%- if message.reasoning_content is string %}
|
| 46 |
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{%- set reasoning_content = message.reasoning_content %}
|
| 47 |
+
{%- else %}
|
| 48 |
+
{%- if '</think>' in content %}
|
| 49 |
+
{%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
|
| 50 |
+
{%- set content = content.split('</think>')[-1].lstrip('\n') %}
|
| 51 |
+
{%- endif %}
|
| 52 |
+
{%- endif %}
|
| 53 |
+
|
| 54 |
+
{%- if message.tool_calls %}
|
| 55 |
+
{%- set content_parts = content.split('<tool_sep>') %}
|
| 56 |
+
{%- set processed_content = content_parts[0] %}
|
| 57 |
+
{%- set tool_calls_count = message.tool_calls|length %}
|
| 58 |
+
{%- set tool_sep_count = content_parts|length - 1 %}
|
| 59 |
+
{%- set min_count = [tool_calls_count, tool_sep_count]|min %}
|
| 60 |
+
|
| 61 |
+
{%- for i in range(1, content_parts|length) %}
|
| 62 |
+
{%- set tool_index = i - 1 %}
|
| 63 |
+
{%- if tool_index < tool_calls_count %}
|
| 64 |
+
{%- set tool_call = message.tool_calls[tool_index] %}
|
| 65 |
+
{%- if tool_call.function %}
|
| 66 |
+
{%- set tool_call = tool_call.function %}
|
| 67 |
+
{%- endif %}
|
| 68 |
+
{%- set single_tool_xml %}
|
| 69 |
+
{{- '<function name="' ~ tool_call.name ~ '">' }}
|
| 70 |
+
{%- if tool_call.arguments %}
|
| 71 |
+
{%- set args_dict = tool_call.arguments %}
|
| 72 |
+
{%- for param_name, param_value in args_dict.items() %}
|
| 73 |
+
{{- '<param name="' ~ param_name ~ '">' }}
|
| 74 |
+
{%- if param_value is string and ('<' in param_value or '&' in param_value or '\n' in param_value) %}
|
| 75 |
+
{{- '<![CDATA[' + param_value + ']]>' }}
|
| 76 |
+
{%- else %}
|
| 77 |
+
{{- param_value }}
|
| 78 |
+
{%- endif %}
|
| 79 |
+
{{- '</param>' }}
|
| 80 |
+
{%- endfor %}
|
| 81 |
+
{%- endif %}
|
| 82 |
+
{{- '</function>' }}
|
| 83 |
+
{%- endset %}
|
| 84 |
+
{%- set processed_content = processed_content + single_tool_xml + content_parts[i] %}
|
| 85 |
+
{%- else %}
|
| 86 |
+
{%- set processed_content = processed_content + content_parts[i] %}
|
| 87 |
+
{%- endif %}
|
| 88 |
+
{%- endfor %}
|
| 89 |
+
|
| 90 |
+
{%- if tool_calls_count > tool_sep_count %}
|
| 91 |
+
{%- for remaining_index in range(tool_sep_count, tool_calls_count) %}
|
| 92 |
+
{%- set tool_call = message.tool_calls[remaining_index] %}
|
| 93 |
+
{%- if tool_call.function %}
|
| 94 |
+
{%- set tool_call = tool_call.function %}
|
| 95 |
+
{%- endif %}
|
| 96 |
+
{%- set remaining_tool_xml %}
|
| 97 |
+
{{- '<function name="' ~ tool_call.name ~ '">' }}
|
| 98 |
+
{%- if tool_call.arguments %}
|
| 99 |
+
{%- set args_dict = tool_call.arguments %}
|
| 100 |
+
{%- for param_name, param_value in args_dict.items() %}
|
| 101 |
+
{{- '<param name="' ~ param_name ~ '">' }}
|
| 102 |
+
{%- if param_value is string and ('<' in param_value or '&' in param_value or '\n' in param_value) %}
|
| 103 |
+
{{- '<![CDATA[' + param_value + ']]>' }}
|
| 104 |
+
{%- else %}
|
| 105 |
+
{{- param_value }}
|
| 106 |
+
{%- endif %}
|
| 107 |
+
{{- '</param>' }}
|
| 108 |
+
{%- endfor %}
|
| 109 |
+
{%- endif %}
|
| 110 |
+
{{- '</function>' }}
|
| 111 |
+
{%- endset %}
|
| 112 |
+
{%- set processed_content = processed_content + remaining_tool_xml %}
|
| 113 |
+
{%- endfor %}
|
| 114 |
+
{%- endif %}
|
| 115 |
+
|
| 116 |
+
{%- set content = processed_content %}
|
| 117 |
+
{%- endif %}
|
| 118 |
+
|
| 119 |
+
{%- if reasoning_content %}
|
| 120 |
+
{{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
|
| 121 |
+
{%- elif '<think>' not in content and '</think>' not in content %}
|
| 122 |
+
{{- '<|im_start|>' + message.role + '\n<think>\n\n</think>\n\n' + content.lstrip('\n') }}
|
| 123 |
+
{%- else %}
|
| 124 |
+
{{- '<|im_start|>' + message.role + '\n' + content }}
|
| 125 |
+
{%- endif %}
|
| 126 |
+
|
| 127 |
+
{%- if message.tool_calls and not has_tool_sep %}
|
| 128 |
+
{%- for tool_call in message.tool_calls %}
|
| 129 |
+
{%- if (loop.first and content) or (not loop.first) %}
|
| 130 |
+
{{- '\n' }}
|
| 131 |
+
{%- endif %}
|
| 132 |
+
{%- if tool_call.function %}
|
| 133 |
+
{%- set tool_call = tool_call.function %}
|
| 134 |
+
{%- endif %}
|
| 135 |
+
{{- '<function name="' ~ tool_call.name ~ '">' }}
|
| 136 |
+
{%- if tool_call.arguments %}
|
| 137 |
+
{%- set args_dict = tool_call.arguments %}
|
| 138 |
+
{%- for param_name, param_value in args_dict.items() %}
|
| 139 |
+
{{- '<param name="' ~ param_name ~ '">' }}
|
| 140 |
+
{%- if param_value is string and ('<' in param_value or '&' in param_value or '\n' in param_value) %}
|
| 141 |
+
{{- '<![CDATA[' + param_value + ']]>' }}
|
| 142 |
+
{%- else %}
|
| 143 |
+
{{- param_value }}
|
| 144 |
+
{%- endif %}
|
| 145 |
+
{{- '</param>' }}
|
| 146 |
+
{%- endfor %}
|
| 147 |
+
{%- endif %}
|
| 148 |
+
{{- '</function>' }}
|
| 149 |
+
{%- endfor %}
|
| 150 |
+
{%- endif %}
|
| 151 |
+
{{- '<|im_end|>\n' }}
|
| 152 |
+
{%- elif message.role == "tool" %}
|
| 153 |
+
{%- if loop.first or (messages[loop.index0 - 1].role != "tool") %}
|
| 154 |
+
{{- '<|im_start|>user' }}
|
| 155 |
+
{%- endif %}
|
| 156 |
+
{{- '\n<tool_response>\n' }}
|
| 157 |
+
{%- if message.content is string %}
|
| 158 |
+
{{- content }}
|
| 159 |
+
{%- else %}
|
| 160 |
+
{{- message.content | tojson(ensure_ascii=False) }}
|
| 161 |
+
{%- endif %}
|
| 162 |
+
{{- '\n</tool_response>' }}
|
| 163 |
+
{%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
|
| 164 |
+
{{- '<|im_end|>\n' }}
|
| 165 |
+
{%- endif %}
|
| 166 |
+
{%- endif %}
|
| 167 |
+
{%- endfor %}
|
| 168 |
+
{%- if add_generation_prompt %}
|
| 169 |
+
{{- '<|im_start|>assistant\n' }}
|
| 170 |
+
{%- if enable_thinking is defined %}
|
| 171 |
+
{%- if enable_thinking is false %}
|
| 172 |
+
{{- '<think>\n\n</think>\n\n' }}
|
| 173 |
+
{%- elif enable_thinking is true %}
|
| 174 |
+
{{- '<think>\n' }}
|
| 175 |
+
{%- endif %}
|
| 176 |
+
{%- endif %}
|
| 177 |
+
{%- endif %}
|
tokenizer.json
ADDED
|
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|
|
|
tokenizer_config.json
ADDED
|
@@ -0,0 +1,17 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
{
|
| 2 |
+
"add_prefix_space": null,
|
| 3 |
+
"backend": "tokenizers",
|
| 4 |
+
"bos_token": "<s>",
|
| 5 |
+
"clean_up_tokenization_spaces": false,
|
| 6 |
+
"eos_token": "</s>",
|
| 7 |
+
"is_local": false,
|
| 8 |
+
"legacy": true,
|
| 9 |
+
"local_files_only": false,
|
| 10 |
+
"model_max_length": 131072,
|
| 11 |
+
"pad_token": "</s>",
|
| 12 |
+
"sp_model_kwargs": {},
|
| 13 |
+
"spaces_between_special_tokens": false,
|
| 14 |
+
"tokenizer_class": "TokenizersBackend",
|
| 15 |
+
"unk_token": "<unk>",
|
| 16 |
+
"use_default_system_prompt": false
|
| 17 |
+
}
|