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 pytorch_model.bin from shawon95/BengaliFakeReviewDetection: direct link, hf CLI and curl.
- Browser
- Download file 443 MB
-
https://huggingface.co/shawon95/BengaliFakeReviewDetection/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://shawon95/BengaliFakeReviewDetection/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/shawon95/BengaliFakeReviewDetection/resolve/main/pytorch_model.bin
443 MB
- Xet hash:
- 01377258aad04bf962b586afac6f8d3dc091c582e368973b4f24b5e286319c5d
- Size of remote file:
- 443 MB
- SHA256:
- f94e6e88eb50d29b2f5b4bad961add12d790062590b70015b30008af0517bae8
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