Instructions to use connectivity/feather_berts_5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_5")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_5") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download hans_eval_bert_5.json from connectivity/feather_berts_5: direct link, hf CLI and curl.
- Browser
- Download file 12.1 MB
-
https://huggingface.co/connectivity/feather_berts_5/resolve/main/hans_eval_bert_5.json
- Command line
-
hf download hf://connectivity/feather_berts_5/hans_eval_bert_5.json
-
curl -L -o hans_eval_bert_5.json https://huggingface.co/connectivity/feather_berts_5/resolve/main/hans_eval_bert_5.json
12.1 MB
- Xet hash:
- 8414d85c8d039b144c7117356a122e6388fe27aa31cef2056a759f7451e28737
- Size of remote file:
- 12.1 MB
- SHA256:
- 2bfd00133f2686acc59dddce1b2ddc32fae5ab2da058e3ade4597a266d7ae96c
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