AI Models
MIST Mini 8B Thinking
MIST family · open weights on Hugging Face.
Reasoning-tuned MIST model trained with GRPO to think step-by-step before answering.
TransformersSafetensorsLlamaText GenerationReasoningGrpoThinkingLlama 3.1MistConversationalEnglishBase: olaverse/MIST-Mini-8BBase: olaverse/MIST-Mini-8BLicence: llama3.1Text Generation InferenceEndpoints Compatible
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343
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May 2026
Created
/ Model card
Built for production use
Open-weights repository on Hugging Face
Integrated ecosystem protocol tier.
Compatible with Transformers library
Integrated ecosystem protocol tier.
Optimised for low-latency inference
Integrated ecosystem protocol tier.
Community engagement: 3 likes
Integrated ecosystem protocol tier.
/ Quick start
Use MIST Mini 8B Thinking, straight from its model card.
example.pyfrom the model card
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained(
"olaverse/MIST-Mini-8B-Thinking",
torch_dtype="auto",
device_map="auto",
)
tokenizer = AutoTokenizer.from_pretrained("olaverse/MIST-Mini-8B-Thinking")
messages = [
{
"role": "system",
"content": "Think step by step inside <think> tags before answering."
},
{
"role": "user",
"content": "If a train travels 120 miles in 2 hours, what is its speed?"
}
]
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=1024, temperature=0.7, do_sample=True)
print(tokenizer.decode(outputs[0], skip_special_tokens=True))
/ Model card
Official repository README
Dynamically loaded from Hugging Face
Model card metadata is available on Hugging Face.
/ Built with
Transformers PyTorch Python
Ready to try MIST Mini 8B Thinking?
Reasoning-tuned MIST model trained with GRPO to think step-by-step before answering.
/ Model ecosystem