Instructions to use tensorlabco/bangla-roberta-64k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tensorlabco/bangla-roberta-64k with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="tensorlabco/bangla-roberta-64k")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("tensorlabco/bangla-roberta-64k") model = AutoModelForMaskedLM.from_pretrained("tensorlabco/bangla-roberta-64k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from tensorlabco/bangla-roberta-64k: direct link, hf CLI and curl.
- Browser
- Download file 5.43 kB
-
https://huggingface.co/tensorlabco/bangla-roberta-64k/resolve/main/training_args.bin
- Command line
-
hf download hf://tensorlabco/bangla-roberta-64k/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/tensorlabco/bangla-roberta-64k/resolve/main/training_args.bin
5.43 kB
- Xet hash:
- 640a06fccbf554f8003e6bbfb7856d194aeeb8b55b2ac6389217a47de3176a1e
- Size of remote file:
- 5.43 kB
- SHA256:
- d3a461fb8833521a3e89f96aabbb21cf849ff72212af6c014831c6110d9d9aa0
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