Instructions to use connectivity/feather_berts_64 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use connectivity/feather_berts_64 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="connectivity/feather_berts_64")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("connectivity/feather_berts_64") model = AutoModelForSequenceClassification.from_pretrained("connectivity/feather_berts_64", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download hans_eval_bert_64.json from connectivity/feather_berts_64: direct link, hf CLI and curl.
- Browser
- Download file 12.1 MB
-
https://huggingface.co/connectivity/feather_berts_64/resolve/main/hans_eval_bert_64.json
- Command line
-
hf download hf://connectivity/feather_berts_64/hans_eval_bert_64.json
-
curl -L -o hans_eval_bert_64.json https://huggingface.co/connectivity/feather_berts_64/resolve/main/hans_eval_bert_64.json
12.1 MB
- Xet hash:
- 48874a0428aeae162bf45d1fbe91e2176a8e16fe42575d83834872c1f8e5bc4b
- Size of remote file:
- 12.1 MB
- SHA256:
- 6b871dfc5bb2f5ebd598707251bd0238853a67e41531ef96b942ffe9d41cb8e7
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