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Model: olaverse/MIST-Mini-8B Source: Original Platform
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README.md
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README.md
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---
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license: llama3.1
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language:
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- en
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pipeline_tag: text-generation
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library_name: transformers
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inference: true
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base_model:
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- NousResearch/Hermes-3-Llama-3.1-8B
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- NousResearch/DeepHermes-3-Llama-3-8B-Preview
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- nvidia/Llama-3.1-Nemotron-Nano-8B-v1
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- deepseek-ai/DeepSeek-R1-Distill-Llama-8B
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tags:
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- merge
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- dare_ties
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- llama
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- llama-3.1
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- mist
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---
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# MIST-1-8B
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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.
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fast, thorough, great for everyday use
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## MIST Model Family
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| Model | Params | Speed | Status |
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|---|---|---|---|
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| **MIST-1-8B** | 8B | ~63 tok/s | ✅ Available |
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| [MIST-1-70B](https://huggingface.co/olaverse/MIST-1-70B) | 70B | ~23 tok/s | ✅ Available |
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| [MIST-1-140B](https://huggingface.co/olaverse/MIST-1-140B) | 140B | ~8 tok/s | ✅ Available |
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---
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## Key Strengths
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- ⚡ **Fastest** — 63 tok/s on H200, great for real-time applications
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- 🧠 **Strong Reasoning** — DeepSeek R1 distillation
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- 💻 **Clean Code** — production-ready with comments
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- 📐 **Math** — accurate step-by-step solving
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- 🤝 **Helpful** — low refusal rate
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- 📦 **Lightweight** — 15GB, runs on consumer GPUs
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---
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## Benchmark Results
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| Task | Speed | Quality |
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|---|---|---|
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| Reasoning | 4.5s | ✅ Correct |
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| Coding | 4.0s | ✅ Clean code |
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| Math | 4.0s | ✅ Step-by-step |
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| General | 4.0s | ✅ Accurate |
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| Instruction | 4.0s | ✅ Precise |
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**Average: 63 tok/s**
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---
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## How to Use
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```python
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from transformers import AutoModelForCausalLM, AutoTokenizer
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model = AutoModelForCausalLM.from_pretrained(
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"olaverse/MIST-Mini-8B",
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torch_dtype="auto",
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device_map="auto",
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)
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tokenizer = AutoTokenizer.from_pretrained("olaverse/MIST-Mini-8B")
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messages = [{"role": "user", "content": "Your question here"}]
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text = tokenizer.apply_chat_template(
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messages, tokenize=False, add_generation_prompt=True
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)
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inputs = tokenizer(text, return_tensors="pt").to("cuda")
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outputs = model.generate(**inputs, max_new_tokens=512)
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print(tokenizer.decode(outputs[0], skip_special_tokens=True))
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```
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## Hardware Requirements
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| Precision | VRAM Required |
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|---|---|
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| bfloat16 | 16GB (RTX 3090/4090) |
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| 4-bit | 6GB (RTX 3060+) |
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---
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## Recommended Generation Settings
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These settings were verified through testing. Without `repetition_penalty`
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and `min_p` the model will ramble and not stop cleanly.
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```python
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outputs = model.generate(
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**inputs,
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max_new_tokens=1024,
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do_sample=True,
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temperature=0.7,
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top_p=0.95,
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min_p=0.05,
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repetition_penalty=1.5,
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eos_token_id=[128040, 128009, 128001],
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pad_token_id=128001,
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)
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```
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### Stop Tokens
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This model's ChatML parents (`<|im_end|>`) survived the DARE+TIES merge
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alongside Llama 3.1 native tokens. Use all three:
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| Token | ID | Source |
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|---|---|---|
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| `<\|im_end\|>` | 128040 | Hermes/Nemotron parents |
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| `<\|eot_id\|>` | 128009 | Llama 3.1 native |
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| `<\|end_of_text\|>` | 128001 | Llama 3.1 native |
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## License
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[Llama 3.1 Community License](https://llama.meta.com/llama3/license/)
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chat_template.jinja
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{% if messages[0]['role'] == 'system' %}{% set system_message = messages[0]['content'] %}{% set messages = messages[1:] %}{% else %}{% set system_message = 'You are a helpful assistant.' %}{% endif %}{{ '<|im_start|>system
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' + system_message + '<|im_end|>
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' }}{% for message in messages %}{% if message['role'] == 'user' %}{{ '<|im_start|>user
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' + message['content'] + '<|im_end|>
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' }}{% elif message['role'] == 'assistant' %}{{ '<|im_start|>assistant
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' + message['content'] + '<|im_end|>
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' }}{% elif message['role'] == 'tool' %}{{ '<|im_start|>tool
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' + message['content'] + '<|im_end|>
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' }}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant
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' }}{% endif %}
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config.json
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config.json
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{
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"architectures": [
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"LlamaForCausalLM"
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"attention_bias": false,
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"bos_token_id": 128000,
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 131072,
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"mlp_bias": false,
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"model_type": "llama",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": {
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"factor": 8.0,
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"high_freq_factor": 4.0,
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"low_freq_factor": 1.0,
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"original_max_position_embeddings": 8192,
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"rope_type": "llama3"
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"rope_theta": 500000.0,
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"tie_word_embeddings": false,
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"transformers_version": "4.57.6",
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"use_cache": true,
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"vocab_size": 128256
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}
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"model.layers.7.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.7.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.7.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.7.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.8.input_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.8.mlp.down_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.8.mlp.gate_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.8.mlp.up_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.8.post_attention_layernorm.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.8.self_attn.k_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.8.self_attn.o_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.8.self_attn.q_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.8.self_attn.v_proj.weight": "model-00001-of-00004.safetensors",
|
||||
"model.layers.9.input_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.mlp.down_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.mlp.gate_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.mlp.up_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.post_attention_layernorm.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.self_attn.k_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.self_attn.o_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.self_attn.q_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.layers.9.self_attn.v_proj.weight": "model-00002-of-00004.safetensors",
|
||||
"model.norm.weight": "model-00004-of-00004.safetensors"
|
||||
}
|
||||
}
|
||||
11
special_tokens_map.json
Normal file
11
special_tokens_map.json
Normal file
@@ -0,0 +1,11 @@
|
||||
{
|
||||
"bos_token": {
|
||||
"content": "<|begin_of_text|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
},
|
||||
"eos_token": "<|im_end|>",
|
||||
"pad_token": "<|end_of_text|>"
|
||||
}
|
||||
6
templates/chat_template.jinja
Normal file
6
templates/chat_template.jinja
Normal file
@@ -0,0 +1,6 @@
|
||||
{{bos_token}}{% for message in messages %}{% if loop.first and messages[0]['role'] != 'system' %}{{ '<|im_start|>system
|
||||
You are a helpful assistant.<|im_end|>
|
||||
' }}{% endif %}{{'<|im_start|>' + message['role'] + '
|
||||
' + message['content'] + '<|im_end|>' + '
|
||||
'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant
|
||||
' }}{% endif %}
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:14b5e679cb69af62e14c3b98d346177bd4137d882a44f87dec9efec982b01a05
|
||||
size 17209403
|
||||
2065
tokenizer_config.json
Normal file
2065
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user