Text Generation
Transformers
TensorBoard
Safetensors
gpt2
Generated from Trainer
text-generation-inference
Instructions to use rafihmd21/humanoid-principal-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rafihmd21/humanoid-principal-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="rafihmd21/humanoid-principal-model")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("rafihmd21/humanoid-principal-model") model = AutoModelForCausalLM.from_pretrained("rafihmd21/humanoid-principal-model") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use rafihmd21/humanoid-principal-model with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "rafihmd21/humanoid-principal-model" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "rafihmd21/humanoid-principal-model", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/rafihmd21/humanoid-principal-model
- SGLang
How to use rafihmd21/humanoid-principal-model 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 "rafihmd21/humanoid-principal-model" \ --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": "rafihmd21/humanoid-principal-model", "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 "rafihmd21/humanoid-principal-model" \ --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": "rafihmd21/humanoid-principal-model", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use rafihmd21/humanoid-principal-model with Docker Model Runner:
docker model run hf.co/rafihmd21/humanoid-principal-model
- Xet hash:
- b7fd92d8db0a35a9290bb8dab8ac903a02dfaf797484e67407570c402f8ae2fa
- Size of remote file:
- 5.91 kB
- SHA256:
- dfc26b93d6f204d9fa62b37985c93d19878592b23b807fac2888effad7f2c104
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