Instructions to use abdo-Mansour/jais-family-2p7b-chat-BnB-8 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abdo-Mansour/jais-family-2p7b-chat-BnB-8 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="abdo-Mansour/jais-family-2p7b-chat-BnB-8", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("abdo-Mansour/jais-family-2p7b-chat-BnB-8", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use abdo-Mansour/jais-family-2p7b-chat-BnB-8 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "abdo-Mansour/jais-family-2p7b-chat-BnB-8" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "abdo-Mansour/jais-family-2p7b-chat-BnB-8", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/abdo-Mansour/jais-family-2p7b-chat-BnB-8
- SGLang
How to use abdo-Mansour/jais-family-2p7b-chat-BnB-8 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 "abdo-Mansour/jais-family-2p7b-chat-BnB-8" \ --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": "abdo-Mansour/jais-family-2p7b-chat-BnB-8", "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 "abdo-Mansour/jais-family-2p7b-chat-BnB-8" \ --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": "abdo-Mansour/jais-family-2p7b-chat-BnB-8", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use abdo-Mansour/jais-family-2p7b-chat-BnB-8 with Docker Model Runner:
docker model run hf.co/abdo-Mansour/jais-family-2p7b-chat-BnB-8
Download pytorch_model.bin from abdo-Mansour/jais-family-2p7b-chat-BnB-8: direct link, hf CLI and curl.
- Browser
- Download file 2.96 GB
-
https://huggingface.co/abdo-Mansour/jais-family-2p7b-chat-BnB-8/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://abdo-Mansour/jais-family-2p7b-chat-BnB-8/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/abdo-Mansour/jais-family-2p7b-chat-BnB-8/resolve/main/pytorch_model.bin
2.96 GB
- Xet hash:
- ccab8421f239a43a1676d4bfd547f5f6d85d00aff9d1751205160552f18baaad
- Size of remote file:
- 2.96 GB
- SHA256:
- 25b2d3f438617927ef7a66feb9b90055154cda61aeb5f699f58ed13fac95d3cd
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