初始化项目，由ModelHub XC社区提供模型

Model: francescofiamingo1/FF_3
Source: Original Platform

README.md

@@ -0,0 +1,78 @@
+---
+license: apache-2.0
+language:
+- en
+library_name: transformers
+pipeline_tag: text-generation
+tags:
+- gpt2
+- causal-lm
+- ff-llm
+---
+
+# FF_3 — FF-LLM 2.02B
+
+FF_3 is a 2.02B parameter language model trained from scratch.
+
+## Model Details
+- **Architecture**: GPT-2 decoder-only (custom)
+- **Parameters**: 2,022,739,072
+- **Vocabulary**: 50,257 (GPT-2 BPE tokenizer)
+- **Context length**: 2,048 tokens
+- **Training**: From scratch on 90B tokens
+
+## Training Pipeline
+1. **Pretraining**: 90B tokens (web + STEM data)
+2. **SFT**: 760K examples + 100K high-quality examples
+3. **DPO**: 38,863 preference pairs
+4. **Distillation**: 20K examples from Qwen2.5-32B teacher
+
+## Prompt Format
+```
+### System:
+You are FF-LLM, a helpful assistant.
+
+### Instruction:
+{your question here}
+
+### Response:
+```
+
+## Usage with Transformers
+
+```python
+from transformers import GPT2LMHeadModel, GPT2Tokenizer
+
+model = GPT2LMHeadModel.from_pretrained("ff-llm/FF_3")
+tokenizer = GPT2Tokenizer.from_pretrained("ff-llm/FF_3")
+
+prompt = (
+    "### System:\nYou are FF-LLM, a helpful assistant.\n\n"
+    "### Instruction:\nWhat is the capital of France?\n\n### Response:\n"
+)
+input_ids = tokenizer.encode(prompt, return_tensors="pt")
+output = model.generate(
+    input_ids, max_new_tokens=256, do_sample=True,
+    temperature=0.7, top_p=0.9,
+    eos_token_id=tokenizer.eos_token_id,
+    pad_token_id=tokenizer.eos_token_id,
+)
+print(tokenizer.decode(output[0][input_ids.shape[1]:], skip_special_tokens=True))
+```
+
+## Usage with Ollama
+```bash
+ollama run ff-llm/FF_3
+```
+
+## Limitations
+- Weak mathematical reasoning
+- May hallucinate on factual questions
+- English only
+
+## Training Cost
+~\,000 total compute cost
+Trained by a single researcher
+
+## License
+Apache 2.0