Instructions to use ram-lexsi/agenttune-testrun-graph-memory with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ram-lexsi/agenttune-testrun-graph-memory with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ram-lexsi/agenttune-testrun-graph-memory", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ram-lexsi/agenttune-testrun-graph-memory: direct link, hf CLI and curl.
- Browser
- Download file 7.38 kB
-
https://huggingface.co/ram-lexsi/agenttune-testrun-graph-memory/resolve/main/training_args.bin
- Command line
-
hf download hf://ram-lexsi/agenttune-testrun-graph-memory/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ram-lexsi/agenttune-testrun-graph-memory/resolve/main/training_args.bin
7.38 kB
- Xet hash:
- 8d5a8f4c0ffa9df03cb03d731efea7d1bcb734cd48f9966f9f2ae6248d904add
- Size of remote file:
- 7.38 kB
- SHA256:
- fa7c306cab019f9d8c79b5f1f8dd8f5a969de571fb088ef412b601449724e11a
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