Instructions to use Ksjsjjdj/Gemmax with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Ksjsjjdj/Gemmax with PEFT:
Task type is invalid.
- Transformers
How to use Ksjsjjdj/Gemmax with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Ksjsjjdj/Gemmax")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Ksjsjjdj/Gemmax", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Ksjsjjdj/Gemmax with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Ksjsjjdj/Gemmax" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Ksjsjjdj/Gemmax", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/Ksjsjjdj/Gemmax
- SGLang
How to use Ksjsjjdj/Gemmax 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 "Ksjsjjdj/Gemmax" \ --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": "Ksjsjjdj/Gemmax", "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 "Ksjsjjdj/Gemmax" \ --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": "Ksjsjjdj/Gemmax", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use Ksjsjjdj/Gemmax with Docker Model Runner:
docker model run hf.co/Ksjsjjdj/Gemmax
- Xet hash:
- 88ba1d4899fd21e08e4eba682747b833adfe5b461030afcc43eaa043dd9a6cc8
- Size of remote file:
- 5.91 kB
- SHA256:
- 3a0b4a579bda333745ebf654ed3d22fd3d8303cbd85c1a0763d6a7a11c4c761a
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