Instructions to use shawon95/BengaliFakeReviewDetection with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shawon95/BengaliFakeReviewDetection with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="shawon95/BengaliFakeReviewDetection")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("shawon95/BengaliFakeReviewDetection") model = AutoModelForSequenceClassification.from_pretrained("shawon95/BengaliFakeReviewDetection", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from shawon95/BengaliFakeReviewDetection: direct link, hf CLI and curl.
- Browser
- Download file 343 Bytes
-
https://huggingface.co/shawon95/BengaliFakeReviewDetection/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://shawon95/BengaliFakeReviewDetection/tokenizer_config.json
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curl -L -o tokenizer_config.json https://huggingface.co/shawon95/BengaliFakeReviewDetection/resolve/main/tokenizer_config.json
343 Bytes
| {"do_lower_case": false, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": false, "strip_accents": null, "special_tokens_map_file": null, "full_tokenizer_file": null, "name_or_path": "csebuetnlp/banglabert", "do_basic_tokenize": true, "never_split": null} |