Instructions to use connectivity/feather_berts_34 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_34 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_34")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_34") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_34", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/feather_berts_34: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/feather_berts_34/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/feather_berts_34/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/feather_berts_34/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 1ba12fa2c78da185f1001cd45bbaf43deb8bbe5b42cf6126bfe75073e749dcdb
- Size of remote file:
- 438 MB
- SHA256:
- cd570efec1ce3e32c815366098e8275c20becf0c03eb84ce29adbdba034881d6
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