Instructions to use jason9693/kcelectra-v2022-dev-apeach with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jason9693/kcelectra-v2022-dev-apeach with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jason9693/kcelectra-v2022-dev-apeach")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jason9693/kcelectra-v2022-dev-apeach") model = AutoModelForSequenceClassification.from_pretrained("jason9693/kcelectra-v2022-dev-apeach", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from jason9693/kcelectra-v2022-dev-apeach: direct link, hf CLI and curl.
- Browser
- Download file 543 Bytes
-
https://huggingface.co/jason9693/kcelectra-v2022-dev-apeach/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://jason9693/kcelectra-v2022-dev-apeach/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/jason9693/kcelectra-v2022-dev-apeach/resolve/main/tokenizer_config.json
543 Bytes
| {"do_lower_case": false, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "do_basic_tokenize": true, "never_split": null, "model_max_length": 512, "special_tokens_map_file": "/root/.cache/huggingface/transformers/06fad5813819d03afddeb292634b52797bd5ee520ffc07b25fdb0edbc8205ae0.31b83c6ab34462cefd974ed0df8dd4189e7b7b81b47315b7a10627f7ae120002", "name_or_path": "beomi/kcelectra-v2022-dev", "tokenizer_class": "BertTokenizer"} |