Instructions to use Atnafu/mt5-base-squad2-fin with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Atnafu/mt5-base-squad2-fin with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Atnafu/mt5-base-squad2-fin") model = AutoModelForSeq2SeqLM.from_pretrained("Atnafu/mt5-base-squad2-fin", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from Atnafu/mt5-base-squad2-fin: direct link, hf CLI and curl.
- Browser
- Download file 2.33 GB
-
https://huggingface.co/Atnafu/mt5-base-squad2-fin/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://Atnafu/mt5-base-squad2-fin@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/Atnafu/mt5-base-squad2-fin/resolve/refs%2Fpr%2F1/pytorch_model.bin
2.33 GB
- Xet hash:
- 9f23986da4a0c67e0a09fb265e39738cf798487a6793ad66caadd952c2fae0c5
- Size of remote file:
- 2.33 GB
- SHA256:
- e3ee5c5022e02547088b7074da8f3c156b00e2bbab91041d6a005460bb201ac0
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