Instructions to use connectivity/feather_berts_17 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_17 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_17")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_17") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_17", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from connectivity/feather_berts_17: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/connectivity/feather_berts_17/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://connectivity/feather_berts_17/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/connectivity/feather_berts_17/resolve/main/pytorch_model.bin
438 MB
- Xet hash:
- 92877665999470f877172158a9d3b0f6ab440d42a43a42338d2b7ca9011e8513
- Size of remote file:
- 438 MB
- SHA256:
- 28846255b25e9171d16ee1edeaba8f6f65f2c7ac12bd97bc1cd66e5c97e2c8f4
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