Instructions to use yevhenkost/classifier__mergedcutiesruns__evidenceAlignment_albert with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use yevhenkost/classifier__mergedcutiesruns__evidenceAlignment_albert with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="yevhenkost/classifier__mergedcutiesruns__evidenceAlignment_albert")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("yevhenkost/classifier__mergedcutiesruns__evidenceAlignment_albert") model = AutoModelForSequenceClassification.from_pretrained("yevhenkost/classifier__mergedcutiesruns__evidenceAlignment_albert", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.safetensors from yevhenkost/classifier__mergedcutiesruns__evidenceAlignment_albert: direct link, hf CLI and curl.
- Browser
- Download file 46.7 MB
-
https://huggingface.co/yevhenkost/classifier__mergedcutiesruns__evidenceAlignment_albert/resolve/refs%2Fpr%2F1/model.safetensors
- Command line
-
hf download hf://yevhenkost/classifier__mergedcutiesruns__evidenceAlignment_albert@refs/pr/1/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/yevhenkost/classifier__mergedcutiesruns__evidenceAlignment_albert/resolve/refs%2Fpr%2F1/model.safetensors
46.7 MB
- Xet hash:
- 93283160efdb4860b538be54c1b58a407ae628c274b613eb6c0f0bdca0d913db
- Size of remote file:
- 46.7 MB
- SHA256:
- 1ca63dcf60bb1459817cd39646aca51872e49e5deae45db8e0f1eb2a50020fd3
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