Instructions to use connectivity/feather_berts_70 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_70 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_70")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_70") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_70", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/feather_berts_70: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/feather_berts_70/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/feather_berts_70/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/feather_berts_70/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 1d2a0231839e78d26218d8074fab5b6da92f9967b6d55238ec4351d129e05614
- Size of remote file:
- 438 MB
- SHA256:
- 0024dc66c24ed6be52de1ce431ef43028bce4d964c020b43487dc1d547ba2e5b
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