初始化项目，由ModelHub XC社区提供模型

Model: olaverse/MIST-Mini-8B
Source: Original Platform

README.md

@@ -0,0 +1,124 @@
+---
+license: llama3.1
+language:
+- en
+pipeline_tag: text-generation
+library_name: transformers
+inference: true
+base_model:
+- NousResearch/Hermes-3-Llama-3.1-8B
+- NousResearch/DeepHermes-3-Llama-3-8B-Preview
+- nvidia/Llama-3.1-Nemotron-Nano-8B-v1
+- deepseek-ai/DeepSeek-R1-Distill-Llama-8B
+tags:
+- merge
+- dare_ties
+- llama
+- llama-3.1
+- mist
+---
+
+![mist models](https://cdn-uploads.huggingface.co/production/uploads/69949cbacd82af728f850c12/WzzrAklKUsaCCTTASicDf.png)
+
+# MIST-1-8B
+
+MIST-1-8B (formerly MIST-Mini) is the smallest and fastest model in the **MIST model family** by [olaverse](https://huggingface.co/olaverse). Built by blending 4 specialized Llama 3.1 8B models using DARE+TIES — delivering strong performance at maximum speed. 
+fast, thorough, great for everyday use
+
+## MIST Model Family
+
+| Model | Params | Speed | Status |
+|---|---|---|---|
+| **MIST-1-8B** | 8B | ~63 tok/s | ✅ Available |
+| [MIST-1-70B](https://huggingface.co/olaverse/MIST-1-70B) | 70B | ~23 tok/s | ✅ Available |
+| [MIST-1-140B](https://huggingface.co/olaverse/MIST-1-140B) | 140B | ~8 tok/s | ✅ Available |
+
+---
+
+## Key Strengths
+
+- ⚡ **Fastest** — 63 tok/s on H200, great for real-time applications
+- 🧠 **Strong Reasoning** — DeepSeek R1 distillation
+- 💻 **Clean Code** — production-ready with comments
+- 📐 **Math** — accurate step-by-step solving
+- 🤝 **Helpful** — low refusal rate
+- 📦 **Lightweight** — 15GB, runs on consumer GPUs
+
+---
+
+## Benchmark Results
+
+| Task | Speed | Quality |
+|---|---|---|
+| Reasoning | 4.5s | ✅ Correct |
+| Coding | 4.0s | ✅ Clean code |
+| Math | 4.0s | ✅ Step-by-step |
+| General | 4.0s | ✅ Accurate |
+| Instruction | 4.0s | ✅ Precise |
+
+**Average: 63 tok/s**
+
+---
+
+## How to Use
+
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+model = AutoModelForCausalLM.from_pretrained(
+    "olaverse/MIST-Mini-8B",
+    torch_dtype="auto",
+    device_map="auto",
+)
+tokenizer = AutoTokenizer.from_pretrained("olaverse/MIST-Mini-8B")
+
+messages = [{"role": "user", "content": "Your question here"}]
+text = tokenizer.apply_chat_template(
+    messages, tokenize=False, add_generation_prompt=True
+)
+inputs = tokenizer(text, return_tensors="pt").to("cuda")
+outputs = model.generate(**inputs, max_new_tokens=512)
+print(tokenizer.decode(outputs[0], skip_special_tokens=True))
+```
+
+## Hardware Requirements
+
+| Precision | VRAM Required |
+|---|---|
+| bfloat16 | 16GB (RTX 3090/4090) |
+| 4-bit | 6GB (RTX 3060+) |
+
+---
+
+## Recommended Generation Settings
+
+These settings were verified through testing. Without `repetition_penalty` 
+and `min_p` the model will ramble and not stop cleanly.
+
+```python
+outputs = model.generate(
+    **inputs,
+    max_new_tokens=1024,
+    do_sample=True,
+    temperature=0.7,
+    top_p=0.95,
+    min_p=0.05,
+    repetition_penalty=1.5,
+    eos_token_id=[128040, 128009, 128001],
+    pad_token_id=128001,
+)
+```
+
+### Stop Tokens
+This model's ChatML parents (`<|im_end|>`) survived the DARE+TIES merge 
+alongside Llama 3.1 native tokens. Use all three:
+
+| Token | ID | Source |
+|---|---|---|
+| `<\|im_end\|>` | 128040 | Hermes/Nemotron parents |
+| `<\|eot_id\|>` | 128009 | Llama 3.1 native |
+| `<\|end_of_text\|>` | 128001 | Llama 3.1 native |
+
+## License
+
+[Llama 3.1 Community License](https://llama.meta.com/llama3/license/)