Instructions to use jrahn/bertsgambit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jrahn/bertsgambit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jrahn/bertsgambit")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jrahn/bertsgambit") model = AutoModelForSequenceClassification.from_pretrained("jrahn/bertsgambit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from jrahn/bertsgambit: direct link, hf CLI and curl.
- Browser
- Download file 269 MB
-
https://huggingface.co/jrahn/bertsgambit/resolve/main/model.safetensors
- Command line
-
hf download hf://jrahn/bertsgambit/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/jrahn/bertsgambit/resolve/main/model.safetensors
269 MB
- Xet hash:
- 02e06527735d1349342ef63eed1d565156816dffb4fbf86a83439cb6ea4130a9
- Size of remote file:
- 269 MB
- SHA256:
- ca4ce3a93c6a4c793b5af2d7724cb2f74bbaa41df9c28f11568408a2ec172e1c
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