Text Generation
Transformers
PyTorch
English
mistral
code
Eval Results (legacy)
text-generation-inference
Instructions to use uukuguy/speechless-code-mistral-7b-v1.0 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use uukuguy/speechless-code-mistral-7b-v1.0 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="uukuguy/speechless-code-mistral-7b-v1.0")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("uukuguy/speechless-code-mistral-7b-v1.0") model = AutoModelForCausalLM.from_pretrained("uukuguy/speechless-code-mistral-7b-v1.0") - Inference
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use uukuguy/speechless-code-mistral-7b-v1.0 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "uukuguy/speechless-code-mistral-7b-v1.0" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "uukuguy/speechless-code-mistral-7b-v1.0", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/uukuguy/speechless-code-mistral-7b-v1.0
- SGLang
How to use uukuguy/speechless-code-mistral-7b-v1.0 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 "uukuguy/speechless-code-mistral-7b-v1.0" \ --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": "uukuguy/speechless-code-mistral-7b-v1.0", "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 "uukuguy/speechless-code-mistral-7b-v1.0" \ --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": "uukuguy/speechless-code-mistral-7b-v1.0", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use uukuguy/speechless-code-mistral-7b-v1.0 with Docker Model Runner:
docker model run hf.co/uukuguy/speechless-code-mistral-7b-v1.0
License
#3
by mrfakename - opened
Hi,
The license of this model is llama2 but it is based on Mistral (Apache 2.0)
Is this intentional or can we use it under Apache?
Thanks!
According to the base model Mistral, license of this model changed to Apache 2.0 now
Thanks!
mrfakename changed discussion status to closed