Instructions to use connectivity/feather_berts_99 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_99 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_99")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_99") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_99", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download hans_eval_bert_99.json from connectivity/feather_berts_99: direct link, hf CLI and curl.
- Browser
- Download file 12.1 MB
-
https://huggingface.co/connectivity/feather_berts_99/resolve/main/hans_eval_bert_99.json
- Command line
-
hf download hf://connectivity/feather_berts_99/hans_eval_bert_99.json
-
curl -L -o hans_eval_bert_99.json https://huggingface.co/connectivity/feather_berts_99/resolve/main/hans_eval_bert_99.json
12.1 MB
- Xet hash:
- 7a9d3702c69bea85ce51b8eab89ef5bb1c602bad7ecd7dc2d54723938af98250
- Size of remote file:
- 12.1 MB
- SHA256:
- f97e2aaaa806349b404e0eb5c7aded9e43dc2380c2d68be8a73a10603089c1cd
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