Instructions to use connectivity/feather_berts_27 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_27 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_27")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_27") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_27", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/feather_berts_27: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/feather_berts_27/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/feather_berts_27/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/feather_berts_27/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 094faab05f300d775c0ba0fe4e7dee08efa0e130a468c26553db13d0234e2ce4
- Size of remote file:
- 438 MB
- SHA256:
- 1a9e446aed0dd0698dca0c9325d4505b3d16e1fc4d5949e50719bf0c61ed1f2e
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