Instructions to use connectivity/feather_berts_79 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_79 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_79")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_79") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_79", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download hans_eval_bert_79.json from connectivity/feather_berts_79: direct link, hf CLI and curl.
- Browser
- Download file 12.1 MB
-
https://huggingface.co/connectivity/feather_berts_79/resolve/main/hans_eval_bert_79.json
- Command line
-
hf download hf://connectivity/feather_berts_79/hans_eval_bert_79.json
-
curl -L -o hans_eval_bert_79.json https://huggingface.co/connectivity/feather_berts_79/resolve/main/hans_eval_bert_79.json
12.1 MB
- Xet hash:
- abccf9b7aebfa8d6f382913bfac85112a948d361dab91c1d452f69b3eaf40a75
- Size of remote file:
- 12.1 MB
- SHA256:
- a3a881e51fb9b2253c23d67fdb36f3534bc1473da7bfa0d25d0591a0032f9c0f
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