初始化项目，由ModelHub XC社区提供模型

Model: YazoPi/snac-llm-full
Source: Original Platform

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README.md

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+---
+base_model: YazoPi/boomu-snac-llm
+library_name: transformers
+model_name: snac-llm-full
+tags:
+- generated_from_trainer
+- trl
+- unsloth
+- sft
+licence: license
+---
+
+# Model Card for snac-llm-full
+
+This model is a fine-tuned version of [YazoPi/boomu-snac-llm](https://huggingface.co/YazoPi/boomu-snac-llm).
+It has been trained using [TRL](https://github.com/huggingface/trl).
+
+## Quick start
+
+```python
+from transformers import pipeline
+
+question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?"
+generator = pipeline("text-generation", model="YazoPi/snac-llm-full", device="cuda")
+output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0]
+print(output["generated_text"])
+```
+
+## Training procedure
+
+[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/kamatep37-maliba-ia/huggingface/runs/z4rm67xs) 
+
+
+This model was trained with SFT.
+
+### Framework versions
+
+- TRL: 0.24.0
+- Transformers: 4.57.6
+- Pytorch: 2.10.0
+- Datasets: 4.3.0
+- Tokenizers: 0.22.2
+
+## Citations
+
+
+
+Cite TRL as:
+    
+```bibtex
+@misc{vonwerra2022trl,
+	title        = {{TRL: Transformer Reinforcement Learning}},
+	author       = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallou{\'e}dec},
+	year         = 2020,
+	journal      = {GitHub repository},
+	publisher    = {GitHub},
+	howpublished = {\url{https://github.com/huggingface/trl}}
+}
+```

config.json

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+{
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+    "LlamaForCausalLM"
+  ],
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+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "dtype": "bfloat16",
+  "eos_token_id": 128001,
+  "head_dim": 128,
+  "hidden_act": "silu",
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+  "initializer_range": 0.02,
+  "intermediate_size": 8192,
+  "max_position_embeddings": 131072,
+  "mlp_bias": false,
+  "model_name": "YazoPi/boomu-snac-llm",
+  "model_type": "llama",
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+  "num_hidden_layers": 28,
+  "num_key_value_heads": 8,
+  "pad_token_id": 128263,
+  "pretraining_tp": 1,
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+    "original_max_position_embeddings": 8192,
+    "rope_type": "llama3"
+  },
+  "rope_theta": 500000.0,
+  "tie_word_embeddings": true,
+  "transformers_version": "4.57.6",
+  "unsloth_fixed": true,
+  "unsloth_version": "2026.3.3",
+  "use_cache": true,
+  "vocab_size": 156938
+}

generation_config.json

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+  "do_sample": true,
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+  ],
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+  "pad_token_id": 128263,
+  "temperature": 0.6,
+  "top_p": 0.9,
+  "transformers_version": "4.57.6"
+}

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+{
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+  ],
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+  "mlp_bias": false,
+  "model_name": "YazoPi/boomu-snac-llm",
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+    "low_freq_factor": 1.0,
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+    "rope_type": "llama3"
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+  "rope_theta": 500000.0,
+  "tie_word_embeddings": true,
+  "transformers_version": "4.57.6",
+  "unsloth_fixed": true,
+  "unsloth_version": "2026.3.3",
+  "use_cache": true,
+  "vocab_size": 156938
+}

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+  "temperature": 0.6,
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