Instructions to use connectivity/feather_berts_31 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_31 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_31")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_31") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_31", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/feather_berts_31: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/feather_berts_31/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/feather_berts_31/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/feather_berts_31/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 6b95f55d8b9549bafc8968800bc5caee71574a99eda9e63c122c02d376570e45
- Size of remote file:
- 438 MB
- SHA256:
- e8d036c1727a2dd0486de9a1c011f31044a1af341899ff8d275605687982c39b
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