Instructions to use dusersad12/HelixLM-PreviewRepo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dusersad12/HelixLM-PreviewRepo with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="dusersad12/HelixLM-PreviewRepo")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("dusersad12/HelixLM-PreviewRepo") model = AutoModelForCausalLM.from_pretrained("dusersad12/HelixLM-PreviewRepo", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use dusersad12/HelixLM-PreviewRepo with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "dusersad12/HelixLM-PreviewRepo" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "dusersad12/HelixLM-PreviewRepo", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/dusersad12/HelixLM-PreviewRepo
- SGLang
How to use dusersad12/HelixLM-PreviewRepo 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 "dusersad12/HelixLM-PreviewRepo" \ --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": "dusersad12/HelixLM-PreviewRepo", "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 "dusersad12/HelixLM-PreviewRepo" \ --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": "dusersad12/HelixLM-PreviewRepo", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use dusersad12/HelixLM-PreviewRepo with Docker Model Runner:
docker model run hf.co/dusersad12/HelixLM-PreviewRepo
Download pytorch_model.bin from dusersad12/HelixLM-PreviewRepo: direct link, hf CLI and curl.
- Browser
- Download file 31 Bytes
-
https://huggingface.co/dusersad12/HelixLM-PreviewRepo/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://dusersad12/HelixLM-PreviewRepo/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/dusersad12/HelixLM-PreviewRepo/resolve/main/pytorch_model.bin
31 Bytes
- Xet hash:
- 63489e27d518d24f4d9fc3688fb4b97a935c81a05ce62e323f5dce53a919e36d
- Size of remote file:
- 31 Bytes
- SHA256:
- ee6dcfa2371b7d24fb2cab339400bc7f433f3036f9d439d64d719e6ff34755bb
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