Instructions to use TheBloke/Mixtral-8x7B-v0.1-GPTQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TheBloke/Mixtral-8x7B-v0.1-GPTQ with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="TheBloke/Mixtral-8x7B-v0.1-GPTQ")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("TheBloke/Mixtral-8x7B-v0.1-GPTQ") model = AutoModelForCausalLM.from_pretrained("TheBloke/Mixtral-8x7B-v0.1-GPTQ") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use TheBloke/Mixtral-8x7B-v0.1-GPTQ with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "TheBloke/Mixtral-8x7B-v0.1-GPTQ" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TheBloke/Mixtral-8x7B-v0.1-GPTQ", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/TheBloke/Mixtral-8x7B-v0.1-GPTQ
- SGLang
How to use TheBloke/Mixtral-8x7B-v0.1-GPTQ 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 "TheBloke/Mixtral-8x7B-v0.1-GPTQ" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TheBloke/Mixtral-8x7B-v0.1-GPTQ", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'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 "TheBloke/Mixtral-8x7B-v0.1-GPTQ" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "TheBloke/Mixtral-8x7B-v0.1-GPTQ", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use TheBloke/Mixtral-8x7B-v0.1-GPTQ with Docker Model Runner:
docker model run hf.co/TheBloke/Mixtral-8x7B-v0.1-GPTQ
The generative output is strange
#11 opened almost 2 years ago
by
tangpeng
Speeds compared to llama_cpp_python?
2
#10 opened over 2 years ago
by
SpaceCowboy850
Unable to start TGI service for TheBloke/Mixtral-8x7B-v0.1-GPTQ with num_shard as 4
#9 opened over 2 years ago
by
swapnil3597
What would be the minimal Sagemaker instance to deploy this model ?
2
#7 opened over 2 years ago
by
CarlosAndrea
ValueError: Unsupported model type mixtral
1
#6 opened over 2 years ago
by
seabasshn
RuntimeError: shape '[32, 8]' is invalid for input of size 0
7
#5 opened over 2 years ago
by
woldeM
Are you going to release mixtral-8x7B-v0.1-awq
👍 4
#4 opened over 2 years ago
by
HelloJiang
Running the model using "pip install auto-gptq" still results in "CUDA extension not installed"
#3 opened over 2 years ago
by
mvetter
TypeError: mixtral isn't supported yet.
2
#2 opened over 2 years ago
by
luv2261
Build AutoGPTQ from source
3
#1 opened over 2 years ago
by
PeePants