Instructions to use connectivity/feather_berts_87 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_87 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_87")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_87") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_87", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/feather_berts_87: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/feather_berts_87/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/feather_berts_87/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/feather_berts_87/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- e4874b172b626f7e8683ec5dbcdd6da76eabb99affe12529c0c18023567f5906
- Size of remote file:
- 438 MB
- SHA256:
- 58a1931b40d5aab61db3b804ac7ee53b545eefa6ace903a4648716549b81f6e6
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