Instructions to use hpcai-tech/grok-1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use hpcai-tech/grok-1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="hpcai-tech/grok-1", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("hpcai-tech/grok-1", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use hpcai-tech/grok-1 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "hpcai-tech/grok-1" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "hpcai-tech/grok-1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/hpcai-tech/grok-1
- SGLang
How to use hpcai-tech/grok-1 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 "hpcai-tech/grok-1" \ --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": "hpcai-tech/grok-1", "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 "hpcai-tech/grok-1" \ --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": "hpcai-tech/grok-1", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use hpcai-tech/grok-1 with Docker Model Runner:
docker model run hf.co/hpcai-tech/grok-1
Upload tokenizer
hello can this be merged?
hello can this be merged?
Yes, it will. We're checking with the author who provided a transfomers-compatible tokenizer in discussions several days ago.
Yes you can merge! As mentioned in another post, this tokenizer matches the original on the entire xnli dataset (all languages)! This PR also adds the slow-tokenizer in case a user wants to fallback on it.
hello can this be merged?
Hey @ehartford , the PR has been merged and you can now directly use the following method to load the tokenizer
tokenizer = AutoTokenizer.from_pretrained("hpcai-tech/grok-1", trust_remote_code=True)
If you have downloaded the model as a repository, you might want to use git pull to get the tokenizer updated.
We have also updated usage case in both model card and our example in ColossalAI GitHub Repository.
