Instructions to use connectivity/feather_berts_84 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_84 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_84")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_84") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_84", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/feather_berts_84: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/feather_berts_84/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/feather_berts_84/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/feather_berts_84/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 7d9b9e7c70c54043598fbcfe62fdc735afe21c7f91b5d89b4cf56e0d571fe0a8
- Size of remote file:
- 438 MB
- SHA256:
- 3f6fe9306f4d0c03f5cb1fac2202ba9c2fe79c4d9e14920f69f78ea5d1b1f47a
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