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 tokenizer_config.json from yevhenkost/classifier__mergedcutiesruns__evidenceAlignment_albert: direct link, hf CLI and curl.
- Browser
- Download file 513 Bytes
-
https://huggingface.co/yevhenkost/classifier__mergedcutiesruns__evidenceAlignment_albert/resolve/main/tokenizer_config.json
- Command line
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hf download hf://yevhenkost/classifier__mergedcutiesruns__evidenceAlignment_albert/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/yevhenkost/classifier__mergedcutiesruns__evidenceAlignment_albert/resolve/main/tokenizer_config.json
513 Bytes
| {"do_lower_case": false, "remove_space": true, "keep_accents": false, "bos_token": "[CLS]", "eos_token": "[SEP]", "unk_token": "<unk>", "sep_token": "[SEP]", "pad_token": "<pad>", "cls_token": "[CLS]", "mask_token": {"content": "[MASK]", "single_word": false, "lstrip": true, "rstrip": false, "normalized": false, "__type": "AddedToken"}, "sp_model_kwargs": {}, "model_max_length": 512, "special_tokens_map_file": null, "name_or_path": "mergedcuties-evidencealignment-model", "tokenizer_class": "AlbertTokenizer"} |