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
| { | |
| "architectures": [ | |
| "Grok1ModelForCausalLM" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "configuration_grok1.Grok1Config", | |
| "AutoModel": "modeling_grok1.Grok1Model", | |
| "AutoModelForCausalLM": "modeling_grok1.Grok1ModelForCausalLM" | |
| }, | |
| "vocab_size": 131072, | |
| "hidden_size": 6144, | |
| "intermediate_size": 32768, | |
| "num_hidden_layers": 64, | |
| "num_attention_heads": 48, | |
| "num_key_value_heads": 8, | |
| "attn_output_multiplier": 0.08838834764831845, | |
| "embedding_multiplier_scale": 78.38367176906169, | |
| "output_multiplier_scale": 0.5773502691896257, | |
| "max_attn_value": 30.0, | |
| "max_position_embeddings": 8192, | |
| "rms_norm_eps": 1e-5, | |
| "use_cache": true, | |
| "pad_token_id": 0, | |
| "bos_token_id": 1, | |
| "eos_token_id": 2, | |
| "tie_word_embeddings": true, | |
| "num_experts_per_tok": 2, | |
| "num_experts": 8, | |
| "output_router_logits": false, | |
| "router_aux_loss_coef": 0.001, | |
| "torch_dtype": "bfloat16", | |
| "transformers_version": "4.35.0" | |
| } |