Instructions to use typeof/mistral-3.3B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use typeof/mistral-3.3B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="typeof/mistral-3.3B") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("typeof/mistral-3.3B") model = AutoModelForCausalLM.from_pretrained("typeof/mistral-3.3B") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use typeof/mistral-3.3B with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "typeof/mistral-3.3B" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "typeof/mistral-3.3B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/typeof/mistral-3.3B
- SGLang
How to use typeof/mistral-3.3B with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "typeof/mistral-3.3B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "typeof/mistral-3.3B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "typeof/mistral-3.3B" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "typeof/mistral-3.3B", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use typeof/mistral-3.3B with Docker Model Runner:
docker model run hf.co/typeof/mistral-3.3B
What's this model?
Is it chopped only or further fine tuned and ready to be used?
Any update @typeof ?
@KnutJaegersberg @mrfakename apologies for the delay... mistakenly made this public 🫠
It is a part of an ongoing research project in model distillation...
Just updated to most recent improvements - feel free to try it out, share, and let us know what you think!
Hopefully will have more details to share soon!
Hi @typeof , thanks for making this model! I see the license is CC-BY instead of Apache. Are you planning to change this, or do you intend to keep it as CC-BY?
I felt like attempting to fine tune it, but I cant use the model that came out of it. some error on sentencepiece side.
It has a high perplexity,
here is minima: [1]5.6161,[2]6.6278,[3]7.0043,
here is mistral-3.3b: [1]79.7248,[2]131.6063,[3]126.4081,
here is marx-3.3b: [1]7.2258,[2]8.3805,[3]9.0478,
output text:
./main -m ~/Storage/typeof_mistral-3.3B/mistral-3.3B-Q4_K_M.gguf -p "I have"
I have been working on my own project lately, but I still need to do some research and work on them as soon as possible. I think we are ready for these new game features for their next game in the series. [end of text]