Instructions to use Pretam/NIOS_Trilingual_Decoder_Biased with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Pretam/NIOS_Trilingual_Decoder_Biased with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("facebook/nllb-200-distilled-600M") model = PeftModel.from_pretrained(base_model, "Pretam/NIOS_Trilingual_Decoder_Biased") - Transformers
How to use Pretam/NIOS_Trilingual_Decoder_Biased with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Pretam/NIOS_Trilingual_Decoder_Biased", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download checkpoint-30630/optimizer.pt from Pretam/NIOS_Trilingual_Decoder_Biased: direct link, hf CLI and curl.
- Browser
- Download file 82 MB
-
https://huggingface.co/Pretam/NIOS_Trilingual_Decoder_Biased/resolve/main/checkpoint-30630/optimizer.pt
- Command line
-
hf download hf://Pretam/NIOS_Trilingual_Decoder_Biased/checkpoint-30630/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/Pretam/NIOS_Trilingual_Decoder_Biased/resolve/main/checkpoint-30630/optimizer.pt
82 MB
- Xet hash:
- bf42977db996537612b163bc0adfaa5e647662b41f74ade8774d2da562d2647c
- Size of remote file:
- 82 MB
- SHA256:
- 7d45d1c4b76aeb1c6ef05fcce5cf1813a5441e8eb73b66d6246da690cb69a65a
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