Instructions to use connectivity/feather_berts_43 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_43 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_43")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_43") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_43", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download hans_eval_bert_43.json from connectivity/feather_berts_43: direct link, hf CLI and curl.
- Browser
- Download file 12.1 MB
-
https://huggingface.co/connectivity/feather_berts_43/resolve/main/hans_eval_bert_43.json
- Command line
-
hf download hf://connectivity/feather_berts_43/hans_eval_bert_43.json
-
curl -L -o hans_eval_bert_43.json https://huggingface.co/connectivity/feather_berts_43/resolve/main/hans_eval_bert_43.json
12.1 MB
- Xet hash:
- 293b50ddbf74ece45b911f00716e3bf573ef0ff85e3a1be69746c5e41ce8577c
- Size of remote file:
- 12.1 MB
- SHA256:
- 9534eceaf941204c79b528abd4d2979aaa1b38cd2a9d4a7086a159d4234efd27
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