Instructions to use AriesChen/GeoLLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use AriesChen/GeoLLM with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="AriesChen/GeoLLM", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("AriesChen/GeoLLM", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download .gitattributes from AriesChen/GeoLLM: direct link, hf CLI and curl.
- Browser
- Download file 307 Bytes
-
https://huggingface.co/AriesChen/GeoLLM/resolve/main/.gitattributes
- Command line
-
hf download hf://AriesChen/GeoLLM/.gitattributes
-
curl -L -o .gitattributes https://huggingface.co/AriesChen/GeoLLM/resolve/main/.gitattributes
307 Bytes
| optimizer.pt filter=lfs diff=lfs merge=lfs -text | |
| pytorch_model.bin filter=lfs diff=lfs merge=lfs -text | |
| ice_text.model filter=lfs diff=lfs merge=lfs -text | |
| rng_state.pth filter=lfs diff=lfs merge=lfs -text | |
| scheduler.pt filter=lfs diff=lfs merge=lfs -text | |
| training_args.bin filter=lfs diff=lfs merge=lfs -text | |