Instructions to use Firmansyah-Ibrahim/mt5_base-silver-standard-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Firmansyah-Ibrahim/mt5_base-silver-standard-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("google/mt5-base") model = PeftModel.from_pretrained(base_model, "Firmansyah-Ibrahim/mt5_base-silver-standard-lora") - Transformers
How to use Firmansyah-Ibrahim/mt5_base-silver-standard-lora with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Firmansyah-Ibrahim/mt5_base-silver-standard-lora", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b7229916ce02ff5c59cc09ffeeb0883741346b6da61282b29d220ff70aab97e4
- Size of remote file:
- 16 MB
- SHA256:
- 5a5297a66fb7b0f18853c4970ed29bb803a786e816cde14e177ff772890e6a84
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.