Instructions to use connectivity/feather_berts_77 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_77 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_77")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_77") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_77", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download hans_eval_bert_77.json from connectivity/feather_berts_77: direct link, hf CLI and curl.
- Browser
- Download file 12.1 MB
-
https://huggingface.co/connectivity/feather_berts_77/resolve/main/hans_eval_bert_77.json
- Command line
-
hf download hf://connectivity/feather_berts_77/hans_eval_bert_77.json
-
curl -L -o hans_eval_bert_77.json https://huggingface.co/connectivity/feather_berts_77/resolve/main/hans_eval_bert_77.json
12.1 MB
- Xet hash:
- 5fcf1addceac7a64d0137ba960a8cdc2246ee44018c71c4775b507d26f9c94fc
- Size of remote file:
- 12.1 MB
- SHA256:
- 6390bb475921091463c86670498a96bf3a97e7b713bdfe69f07a70fee5e6b830
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