Instructions to use jysssacc/mt0-base_fine_lr5e-06_bs4_epoch5_wd0.01 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jysssacc/mt0-base_fine_lr5e-06_bs4_epoch5_wd0.01 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("jysssacc/mt0-base_fine_lr5e-06_bs4_epoch5_wd0.01") model = AutoModelForSeq2SeqLM.from_pretrained("jysssacc/mt0-base_fine_lr5e-06_bs4_epoch5_wd0.01", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from jysssacc/mt0-base_fine_lr5e-06_bs4_epoch5_wd0.01: direct link, hf CLI and curl.
- Browser
- Download file 16.3 MB
-
https://huggingface.co/jysssacc/mt0-base_fine_lr5e-06_bs4_epoch5_wd0.01/resolve/main/tokenizer.json
- Command line
-
hf download hf://jysssacc/mt0-base_fine_lr5e-06_bs4_epoch5_wd0.01/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/jysssacc/mt0-base_fine_lr5e-06_bs4_epoch5_wd0.01/resolve/main/tokenizer.json
16.3 MB
- Xet hash:
- 335e7fa7282244cb1e4d279595853cb260b12bf6bedf83b205b68bd0edd1e906
- Size of remote file:
- 16.3 MB
- SHA256:
- 54e5c72a5ea09da48b2f316760b8bc5a445683ab9a5bc6b68db5d8db624ecceb
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