Instructions to use connectivity/feather_berts_67 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_67 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_67")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_67") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_67", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/feather_berts_67: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/feather_berts_67/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/feather_berts_67/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/feather_berts_67/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 48ef48f86615e6387b86fa50163ab9b858e649fde0b5862f4ae561c7e976aec3
- Size of remote file:
- 438 MB
- SHA256:
- c9b2e78b75aa4c790457a0535c719ba68049a4b2c450ed52bb05b00c802fe6ee
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