Instructions to use jasminejwebb/KeywordIdentifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jasminejwebb/KeywordIdentifier with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="jasminejwebb/KeywordIdentifier")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("jasminejwebb/KeywordIdentifier") model = AutoModelForTokenClassification.from_pretrained("jasminejwebb/KeywordIdentifier", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from jasminejwebb/KeywordIdentifier: direct link, hf CLI and curl.
- Browser
- Download file 519 Bytes
-
https://huggingface.co/jasminejwebb/KeywordIdentifier/resolve/refs%2Fpr%2F1/tokenizer_config.json
- Command line
-
hf download hf://jasminejwebb/KeywordIdentifier@refs/pr/1/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/jasminejwebb/KeywordIdentifier/resolve/refs%2Fpr%2F1/tokenizer_config.json
519 Bytes
| {"do_lower_case": false, "remove_space": true, "keep_accents": false, "bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "sep_token": "<sep>", "pad_token": "<pad>", "cls_token": "<cls>", "mask_token": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "additional_special_tokens": ["<eop>", "<eod>"], "special_tokens_map_file": null, "name_or_path": "./reddit_ner/reddit-nerxlnet-base-cased.model/", "tokenizer_class": "XLNetTokenizer"} |