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 model.safetensors from jysssacc/mt0-base_fine_lr5e-06_bs4_epoch5_wd0.01: direct link, hf CLI and curl.
- Browser
- Download file 2.33 GB
-
https://huggingface.co/jysssacc/mt0-base_fine_lr5e-06_bs4_epoch5_wd0.01/resolve/main/model.safetensors
- Command line
-
hf download hf://jysssacc/mt0-base_fine_lr5e-06_bs4_epoch5_wd0.01/model.safetensors
-
curl -L -o model.safetensors https://huggingface.co/jysssacc/mt0-base_fine_lr5e-06_bs4_epoch5_wd0.01/resolve/main/model.safetensors
2.33 GB
- Xet hash:
- 84ce4b2f937b16c6c7df2c28cecb77d45fae248995fc08a6a5f279ea31d53655
- Size of remote file:
- 2.33 GB
- SHA256:
- e5764d6f22f1628e3e74e0dd9cc61bdd3d0f30aa9e2e104e653e7ccd6328ea5c
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