Instructions to use aiplanet/effi-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use aiplanet/effi-7b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="aiplanet/effi-7b")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("aiplanet/effi-7b") model = AutoModelForCausalLM.from_pretrained("aiplanet/effi-7b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use aiplanet/effi-7b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "aiplanet/effi-7b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "aiplanet/effi-7b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/aiplanet/effi-7b
- SGLang
How to use aiplanet/effi-7b 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 "aiplanet/effi-7b" \ --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": "aiplanet/effi-7b", "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 "aiplanet/effi-7b" \ --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": "aiplanet/effi-7b", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use aiplanet/effi-7b with Docker Model Runner:
docker model run hf.co/aiplanet/effi-7b
Commit History
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Update README.md (#4)
Chanukya Patnaik +1: jaintarunAI - Update README.md (038fc9ed72fe5c104650136830d995be230e32a1) Co-authored-by: Tarun Jain <jaintarunAI@users.noreply.huggingface.co>a630988
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Librarian Bot: Add base_model information to model (#3)
Chanukya Patnaik +1: librarian-bot - Librarian Bot: Add base_model information to model (3aec67b4d398fc12a40189b96d17d7f00dfc241d) Co-authored-by: Librarian Bot (Bot) <librarian-bot@users.noreply.huggingface.co>7d2b715
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metadata UI updated (#1)
Chanukya Patnaik +1: lucifertrj - metadata UI updated (a54c11ea29ea71f7ff8ba0f5cf5ed4e4385ca6f4) Co-authored-by: Tarun Jain <lucifertrj@users.noreply.huggingface.co>42fa1bc -
add config.json => need to update model name (#2)
Chanukya Patnaik +1: lucifertrj - add config.json => need to update model name (077407639f16e9cf331fd8a8813a2375f8570d22) Co-authored-by: Tarun Jain <lucifertrj@users.noreply.huggingface.co>93bd7e6
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updated readme
Chanukya Patnaikd58c62e
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Upload model
5feaf84 -
initial commit
c82b7b3