Instructions to use connectivity/feather_berts_59 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_59 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_59")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_59") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_59", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/feather_berts_59: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/feather_berts_59/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/feather_berts_59/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/feather_berts_59/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- c0046c0047cf21d09e1e11570b9b1c202619ac032f00be40f47c9f703a1e92f0
- Size of remote file:
- 438 MB
- SHA256:
- 4a357e0b610d70517e9b55c98450357b488be223939845e89ff32de5f8d8cd8b
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