Instructions to use connectivity/feather_berts_11 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_11 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_11")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_11") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_11", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/feather_berts_11: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/feather_berts_11/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/feather_berts_11/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/feather_berts_11/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- ace5bca5139590265e2edc34ba627c1036eea56d3ddc8042b002040c0f48506b
- Size of remote file:
- 438 MB
- SHA256:
- 8a66c3abdd6100122815a3a5d09ce1e5d8126ad63fd0d8c8ab3c46b7124c0ff2
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