Instructions to use formulae/7B-Dorflan with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use formulae/7B-Dorflan with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="formulae/7B-Dorflan")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("formulae/7B-Dorflan") model = AutoModelForCausalLM.from_pretrained("formulae/7B-Dorflan", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use formulae/7B-Dorflan with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "formulae/7B-Dorflan" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "formulae/7B-Dorflan", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/formulae/7B-Dorflan
- SGLang
How to use formulae/7B-Dorflan 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 "formulae/7B-Dorflan" \ --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": "formulae/7B-Dorflan", "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 "formulae/7B-Dorflan" \ --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": "formulae/7B-Dorflan", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use formulae/7B-Dorflan with Docker Model Runner:
docker model run hf.co/formulae/7B-Dorflan
Commit History
-
Adding Evaluation Results (#1)
- Adding Evaluation Results (6eb26218a3409cacc3c9caf24ca24634d2b19896) Co-authored-by: Open LLM Leaderboard PR Bot <leaderboard-pr-bot@users.noreply.huggingface.co>c8c8772
-
Update README.md
723d96c -
Update README.md
5b40abb -
Update README.md
a7af56c
-
Upload pytorch_model.bin.index.json
5d8e7e5 -
Update README.md
1c398ba -
Update README.md
6a13e62 -
Update README.md
cf9e4b3 -
Update README.md
6561746 -
Update README.md
de5d5cf -
Upload pytorch_model-00001-of-00002.bin with huggingface_hub
adaba8a -
Upload config.json
b0f90a8 -
Upload 4 files
bd9d8a8 -
Upload pytorch_model-00002-of-00002.bin with huggingface_hub
afec765 -
initial commit
2103261