Instructions to use connectivity/feather_berts_24 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_24 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_24")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_24") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_24", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/feather_berts_24: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/feather_berts_24/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/feather_berts_24/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/feather_berts_24/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 51c5342ca4d6737a3e6c55634b38d9ac622ac3bcef625be75c75b4c3b3bb2c49
- Size of remote file:
- 438 MB
- SHA256:
- 923f6f7e352bc5d29d1bfc72dce105fbcad0fc61169b762696a9f1e668309e26
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