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_config.json from Sk4467/Bengali_translator: direct link, hf CLI and curl.
- Browser
- Download file 544 Bytes
-
https://huggingface.co/Sk4467/Bengali_translator/resolve/11372d39e674be4536df57e91baba9ec9ad4e528/tokenizer_config.json
- Command line
-
hf download hf://Sk4467/Bengali_translator@11372d39e674be4536df57e91baba9ec9ad4e528/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/Sk4467/Bengali_translator/resolve/11372d39e674be4536df57e91baba9ec9ad4e528/tokenizer_config.json
544 Bytes
- Xet hash:
- 1d3a8a51b369da7fd6379c0ae09a318fdb66c38ef3c04ea10309ae935667ee2a
- Size of remote file:
- 544 Bytes
- SHA256:
- ddf411c9f790d081e72de76bb8e8b714d74e160e61bc10c9bd8f56022dcd7fd7
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