Instructions to use ArmelR/doremi-280m-opt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ArmelR/doremi-280m-opt with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="ArmelR/doremi-280m-opt")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("ArmelR/doremi-280m-opt") model = AutoModelForCausalLM.from_pretrained("ArmelR/doremi-280m-opt") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use ArmelR/doremi-280m-opt with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "ArmelR/doremi-280m-opt" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "ArmelR/doremi-280m-opt", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/ArmelR/doremi-280m-opt
- SGLang
How to use ArmelR/doremi-280m-opt 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 "ArmelR/doremi-280m-opt" \ --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": "ArmelR/doremi-280m-opt", "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 "ArmelR/doremi-280m-opt" \ --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": "ArmelR/doremi-280m-opt", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use ArmelR/doremi-280m-opt with Docker Model Runner:
docker model run hf.co/ArmelR/doremi-280m-opt
- Xet hash:
- f641a9d80986155e42eb5759dbfc0ec036ac34a92456c1eedc40555aacc66e1b
- Size of remote file:
- 494 MB
- SHA256:
- 55d2c5b506b8b0f20b4e85758c71a1f92718c0b5ca2a4f704eec28cd8c92f289
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.