Instructions to use connectivity/feather_berts_68 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_68 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_68")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_68") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_68", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/feather_berts_68: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/feather_berts_68/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/feather_berts_68/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/feather_berts_68/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 1ff325e0125f6b9dc11ea1821fcc8653d590aaf507d87c70c2da09786f2d27cf
- Size of remote file:
- 438 MB
- SHA256:
- 95d25ace9ed12a83835059a4e8ab09d408623669d0ab472e99adca4455b31b20
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