Instructions to use connectivity/feather_berts_4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_4 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_4")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_4") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_4", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download hans_eval_bert_4.json from connectivity/feather_berts_4: direct link, hf CLI and curl.
- Browser
- Download file 12.1 MB
-
https://huggingface.co/connectivity/feather_berts_4/resolve/main/hans_eval_bert_4.json
- Command line
-
hf download hf://connectivity/feather_berts_4/hans_eval_bert_4.json
-
curl -L -o hans_eval_bert_4.json https://huggingface.co/connectivity/feather_berts_4/resolve/main/hans_eval_bert_4.json
12.1 MB
- Xet hash:
- b17731be6c3b33cbcb7bcccad4307e145c9a75069fa5f5e85706d3e39a0b9978
- Size of remote file:
- 12.1 MB
- SHA256:
- fa42a2dbb754b1cb6666fce41e753bd09ef790cafaffc2b20a24b58555b30b3a
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