Instructions to use g-ronimo/mamba-1.4b-OA with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use g-ronimo/mamba-1.4b-OA with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="g-ronimo/mamba-1.4b-OA")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("g-ronimo/mamba-1.4b-OA", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use g-ronimo/mamba-1.4b-OA with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "g-ronimo/mamba-1.4b-OA" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "g-ronimo/mamba-1.4b-OA", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/g-ronimo/mamba-1.4b-OA
- SGLang
How to use g-ronimo/mamba-1.4b-OA 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 "g-ronimo/mamba-1.4b-OA" \ --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": "g-ronimo/mamba-1.4b-OA", "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 "g-ronimo/mamba-1.4b-OA" \ --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": "g-ronimo/mamba-1.4b-OA", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use g-ronimo/mamba-1.4b-OA with Docker Model Runner:
docker model run hf.co/g-ronimo/mamba-1.4b-OA
Download pytorch_model.bin from g-ronimo/mamba-1.4b-OA: direct link, hf CLI and curl.
- Browser
- Download file 2.75 GB
-
https://huggingface.co/g-ronimo/mamba-1.4b-OA/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://g-ronimo/mamba-1.4b-OA/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/g-ronimo/mamba-1.4b-OA/resolve/main/pytorch_model.bin
2.75 GB
- Xet hash:
- c12dfb7faf13c160627d728f46bb3581e01abfd270d7022392c059ed804737dd
- Size of remote file:
- 2.75 GB
- SHA256:
- 279c11c7d6ffb9750bf06e0763a9b03bb710dad04b4e7f4ccaecd48978714142
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