初始化项目，由ModelHub XC社区提供模型

Model: prathamkode/particle-1.0
Source: Original Platform

README.md

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+---
+license: mit
+language:
+- en
+library_name: transformers
+pipeline_tag: text-generation
+tags:
+- llama
+- from-scratch
+- smol
+datasets:
+- HuggingFaceTB/smol-smoltalk
+- HuggingFaceFW/fineweb_edu_100BT-shuffled
+---
+
+# particle-1.0
+
+~100M-parameter Llama-style chat model trained **from scratch** (random init). Not a fine-tune of Llama, SmolLM, or any Hub base.
+
+Weights are MIT. Training data still needs attribution (below).
+
+## Usage
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+repo = "prathamkode/particle-1.0"
+tok = AutoTokenizer.from_pretrained(repo)
+model = AutoModelForCausalLM.from_pretrained(repo)
+
+messages = [{"role": "user", "content": "hello"}]
+prompt = tok.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+ids = tok(prompt, return_tensors="pt")
+out = model.generate(**ids, max_new_tokens=64, temperature=0.7)
+print(tok.decode(out[0], skip_special_tokens=False))
+```
+
+Chat format:
+
+```
+<|user|>
+hello
+<|assistant|>
+```
+
+## Model details
+
+| | |
+|---|---|
+| Architecture | Llama-style decoder (RoPE, SwiGLU, RMSNorm, tied embeddings) |
+| Parameters | ~100M (12 layers, 768 hidden, 12 heads) |
+| Context | 2048 tokens |
+| Tokenizer | Custom 32k byte-level BPE (not Llama / GPT-2 vocab) |
+| Init | Random `N(0, 0.02)` — trained from scratch |
+| Precision | BF16 training; Hub weights `bfloat16` |
+
+## Training
+
+1. **Tokenizer** trained from scratch on a FineWeb-Edu sample (~2GB text).
+2. **Pretrain** next-token prediction on [`HuggingFaceFW/fineweb_edu_100BT-shuffled`](https://huggingface.co/datasets/HuggingFaceFW/fineweb_edu_100BT-shuffled), first ~2B tokens.
+3. **SFT** on [`HuggingFaceTB/smol-smoltalk`](https://huggingface.co/datasets/HuggingFaceTB/smol-smoltalk) (first user/assistant turn + a few greeting seeds).
+
+SFT used that dataset as **text only**. No teacher model weights were copied.
+
+## Intended use
+
+Research / demo small chat model. Expect short replies, mistakes, and weak reasoning.
+
+## Limitations
+
+- Very small capacity
+- May hallucinate
+- English-centric FineWeb-Edu subset
+- No RLHF / preference tuning
+
+## License
+
+- **These weights:** [MIT](LICENSE)
+- **FineWeb-Edu:** ODC-By (attribute)
+- **smol-smoltalk:** follow the dataset card