Instructions to use CARD-AI/mt5-abstractive-v3-lt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use CARD-AI/mt5-abstractive-v3-lt with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("google/mt5-base") model = PeftModel.from_pretrained(base_model, "CARD-AI/mt5-abstractive-v3-lt") - Transformers
How to use CARD-AI/mt5-abstractive-v3-lt with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("CARD-AI/mt5-abstractive-v3-lt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from CARD-AI/mt5-abstractive-v3-lt: direct link, hf CLI and curl.
- Browser
- Download file 16.4 MB
-
https://huggingface.co/CARD-AI/mt5-abstractive-v3-lt/resolve/main/tokenizer.json
- Command line
-
hf download hf://CARD-AI/mt5-abstractive-v3-lt/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/CARD-AI/mt5-abstractive-v3-lt/resolve/main/tokenizer.json
16.4 MB
- Xet hash:
- 11e181c41bcbec5cc3b61970b537818caff13f05b493b6c94093e5f80ae9a242
- Size of remote file:
- 16.4 MB
- SHA256:
- 3a98a560351a11adf43cd9180e64eec3e393e3bef2ffef5ae1151a0c19ead9e4
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