Instructions to use Ashfaq-06/tinystarcoder-rlhf-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ashfaq-06/tinystarcoder-rlhf-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Ashfaq-06/tinystarcoder-rlhf-model")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Ashfaq-06/tinystarcoder-rlhf-model") model = AutoModelForCausalLM.from_pretrained("Ashfaq-06/tinystarcoder-rlhf-model") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use Ashfaq-06/tinystarcoder-rlhf-model with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Ashfaq-06/tinystarcoder-rlhf-model" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Ashfaq-06/tinystarcoder-rlhf-model", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Ashfaq-06/tinystarcoder-rlhf-model
- SGLang
How to use Ashfaq-06/tinystarcoder-rlhf-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 "Ashfaq-06/tinystarcoder-rlhf-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": "Ashfaq-06/tinystarcoder-rlhf-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 "Ashfaq-06/tinystarcoder-rlhf-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": "Ashfaq-06/tinystarcoder-rlhf-model", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Ashfaq-06/tinystarcoder-rlhf-model with Docker Model Runner:
docker model run hf.co/Ashfaq-06/tinystarcoder-rlhf-model
File size: 445 Bytes
a6d6e6b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | {
"<commit_after>": 17,
"<commit_before>": 15,
"<commit_msg>": 16,
"<empty_output>": 14,
"<filename>": 5,
"<fim_middle>": 2,
"<fim_pad>": 4,
"<fim_prefix>": 1,
"<fim_suffix>": 3,
"<gh_stars>": 6,
"<issue_closed>": 9,
"<issue_comment>": 8,
"<issue_start>": 7,
"<jupyter_code>": 12,
"<jupyter_output>": 13,
"<jupyter_start>": 10,
"<jupyter_text>": 11,
"<reponame>": 18,
"<|endoftext|>": 0,
"[PAD]": 49152
}
|