Update README.md

README.md

@@ -50,133 +50,6 @@ the underlying Qwen3.8 architecture supports image and video inputs.
 | Fine-tuning data | Text-only conversational and instruction data |
 | Supported languages in the prepared data | 13 |
 
-## Intended Capabilities
-
-The training data targets the following behaviors:
-
-- Identify the assistant as XION and attribute its development to PIXELZX.
-- Distinguish XION from ChatGPT, Claude, Gemini, GPT-4, and other third-party
-  models.
-- Hold conversations in Arabic, Chinese, Dutch, English, French, German,
-  Indonesian, Japanese, Korean, Portuguese, Russian, Thai, and Vietnamese.
-- Follow system-prompt personas such as secretary, friend, and teacher styles.
-- Produce direct answers as well as responses containing Qwen-style reasoning
-  sections.
-- Answer factual questions about AI companies and model identities without
-  confusing those entities with XION.
-- Learn selected coding and agent-style interaction patterns from a small
-  Fable-5 subset.
-
-These are training objectives, not guarantees of reliable performance.
-
-## Multi-Token Prediction
-
-The Qwen3.8 architecture includes Multi-Token Prediction (MTP) components.
-However, the Together AI fine-tuning API does not expose a separate MTP loss or
-MTP training switch. The current recipe is standard SFT and must not be
-described as additional MTP fine-tuning.
-
-## Training Data
-
-The current Together AI export is stored in
-`data/together/{train,val}.jsonl`. It uses pre-rendered Qwen3.8 ChatML in the
-instruction format, with one `prompt` and one `completion` field per line.
-
-| Dataset | Train | Validation | Purpose |
-| --- | ---: | ---: | --- |
-| `qwen3_identity` | 1,235 | 156 | Identity and third-party knowledge examples |
-| `qwen3_identity_nothink` | 624 | 78 | Direct identity and knowledge responses |
-| `qwen3_persona` | 858 | 78 | System-prompt persona conversations |
-| `qwen3_uncensored` | 214 | 26 | Low-refusal and open-ended response examples |
-| `fable5` | 40 | 2 | Quality-ranked agent traces flattened to text |
-| **Total** | **2,971** | **340** | |
-
-The prepared data covers Arabic, Chinese, English, French, German, Indonesian,
-Japanese, Korean, Portuguese, Russian, Spanish, Thai, and Vietnamese. Some
-examples contain reasoning traces. The Fable-5 traces are serialized as text;
-they are not native Together function-calling examples.
-
-The Together export is capped at 28,000 rendered tokens per example to leave a
-safety margin below the 32,768-token Qwen3.8 SFT context limit used by Together
-AI. The underlying Qwen3.8 model has a larger native context window, but that
-does not increase the context limit of this Together training job.
-
-## Training Recipe
-
-The current release candidate was prepared for the following Together AI SFT
-configuration:
-
-- Three training epochs.
-- Three validation evaluations.
-- LoRA by default, unless full fine-tuning is selected explicitly.
-- A held-out validation file at `data/together/val.jsonl`.
-- Qwen3.8 ChatML rendered locally before upload.
-
-The pre-rendered `prompt`/`completion` format is intentional. Uploading the
-older `messages` export can cause Together's Qwen3.8 chat-template processing
-to fail with `No user query found in messages`.
-
-## Usage with Transformers
-
-After the XION checkpoint is published, replace `MODEL_ID` with its Hugging
-Face repository ID.
-
-```bash
-pip install -U transformers torch accelerate
-```
-
-```python
-from transformers import AutoModelForMultimodalLM, AutoProcessor
-
-MODEL_ID = "YOUR_ORG/XION-0.2-27B"
-
-processor = AutoProcessor.from_pretrained(MODEL_ID)
-model = AutoModelForMultimodalLM.from_pretrained(
-    MODEL_ID,
-    device_map="auto",
-    torch_dtype="auto",
-)
-
-messages = [
-    {
-        "role": "user",
-        "content": [{"type": "text", "text": "Who are you?"}],
-    }
-]
-
-inputs = processor.apply_chat_template(
-    messages,
-    add_generation_prompt=True,
-    tokenize=True,
-    return_dict=True,
-    return_tensors="pt",
-).to(model.device)
-
-outputs = model.generate(**inputs, max_new_tokens=256)
-new_tokens = outputs[0][inputs["input_ids"].shape[-1] :]
-print(processor.decode(new_tokens, skip_special_tokens=True))
-```
-
-Qwen3.8-based models use thinking mode by default. The exact controls for
-thinking, reasoning effort, and preserved thinking depend on the serving
-framework. Follow the documentation for the selected Transformers, vLLM,
-SGLang, or API runtime before changing those settings.
-
-## Together AI Export
-
-The generated files can be uploaded with the Together CLI:
-
-```bash
-tg files upload data/together/train.jsonl
-```
-
-Use the new file IDs when creating an SFT job. Do not reuse an ID for an older
-`messages`-format file.
-
-The local Together SDK checks pass for both exported files. Server-side
-validation still occurs after upload and should reach `COMPLETED` before a
-training job is started.
-
 ## Limitations and Safety
 
 - XION 0.2 27B is experimental and has no independent benchmark results in