Instructions to use Sk4467/Bengali_translator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Sk4467/Bengali_translator with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="Sk4467/Bengali_translator")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Sk4467/Bengali_translator", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Sk4467/Bengali_translator: direct link, hf CLI and curl.
- Browser
- Download file 17.3 MB
-
https://huggingface.co/Sk4467/Bengali_translator/resolve/main/tokenizer.json
- Command line
-
hf download hf://Sk4467/Bengali_translator/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Sk4467/Bengali_translator/resolve/main/tokenizer.json
17.3 MB
- Xet hash:
- 53d8309df2fdb542ca2a165f635d2083b23bdb60d267efd30938d65c0026cfa5
- Size of remote file:
- 17.3 MB
- SHA256:
- 8a7c59dfb56765f10223e438af158ced1749684762eb109d874df6de15fa6c8f
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