Translation
Transformers
PyTorch
Safetensors
IndicTrans
text2text-generation
indictrans2
ai4bharat
multilingual
custom_code
Instructions to use ai4bharat/indictrans2-en-indic-1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ai4bharat/indictrans2-en-indic-1B with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # 'pip install "transformers<5.0.0' from transformers import pipeline pipe = pipeline("translation", model="ai4bharat/indictrans2-en-indic-1B", trust_remote_code=True)# Load model directly from transformers import AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("ai4bharat/indictrans2-en-indic-1B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Trouble exporting AI4Bharat IndicTrans2 model to ONNX using Optimum
#14
by harshhh17 - opened
I'm working on a project to create an offline, browser-based English-to-Hindi translation app. For this, I'm trying to use the ai4bharat/indictrans2-en-indic-1B model.
My goal is to convert the model from its Hugging Face PyTorch format to ONNX, which I can then run in a web browser using WebAssembly.
I've been trying to use the optimum library to perform this conversion, but I'm running into a series of errors, which seems to be related to the model's custom architecture and the optimum library's API.
What I have tried so far:
- Using optimum-cli: The command-line tool failed with unrecognized arguments and ValueErrors.
- Changing arguments: I have tried various combinations of arguments, such as using output-dir instead of output, and changing fp16=True to dtype="fp16". The TypeErrors seem to persist regardless.
- Manual Conversion: I have tried using torch.onnx.export directly, but this also caused errors with the model's custom tokenizer.