Instructions to use connectivity/feather_berts_72 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_72 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_72")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_72") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_72", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download hans_eval_bert_72.json from connectivity/feather_berts_72: direct link, hf CLI and curl.
- Browser
- Download file 12.1 MB
-
https://huggingface.co/connectivity/feather_berts_72/resolve/main/hans_eval_bert_72.json
- Command line
-
hf download hf://connectivity/feather_berts_72/hans_eval_bert_72.json
-
curl -L -o hans_eval_bert_72.json https://huggingface.co/connectivity/feather_berts_72/resolve/main/hans_eval_bert_72.json
12.1 MB
- Xet hash:
- 9c9388109c2350679e628511b740b14e86c1e95b87c73e6fafdc59acd0077c34
- Size of remote file:
- 12.1 MB
- SHA256:
- 7830263ca540d3f19d00e5de20bbcadc0b47858a0aeaa70518d12f50ae6530f1
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