Instructions to use sbmaruf/bengali_t5_base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sbmaruf/bengali_t5_base with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sbmaruf/bengali_t5_base") model = AutoModelForSeq2SeqLM.from_pretrained("sbmaruf/bengali_t5_base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download flax_model.msgpack from sbmaruf/bengali_t5_base: direct link, hf CLI and curl.
- Browser
- Download file 892 MB
-
https://huggingface.co/sbmaruf/bengali_t5_base/resolve/main/flax_model.msgpack
- Command line
-
hf download hf://sbmaruf/bengali_t5_base/flax_model.msgpack
-
curl -L -o flax_model.msgpack https://huggingface.co/sbmaruf/bengali_t5_base/resolve/main/flax_model.msgpack
892 MB
- Xet hash:
- d0b1f88d3178e15bcd2d4b881f2a648c7a29a2648fd8593ba178876352f479e2
- Size of remote file:
- 892 MB
- SHA256:
- a8417210048cfd6f6a8b18a598236b4205444d0bf2a97372f4b56d9257be5e92
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