Instructions to use ar5entum/bart_eng_hin_mt with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ar5entum/bart_eng_hin_mt with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ar5entum/bart_eng_hin_mt") model = AutoModelForSeq2SeqLM.from_pretrained("ar5entum/bart_eng_hin_mt", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download predict_results.json from ar5entum/bart_eng_hin_mt: direct link, hf CLI and curl.
- Browser
- Download file 292 Bytes
-
https://huggingface.co/ar5entum/bart_eng_hin_mt/resolve/main/predict_results.json
- Command line
-
hf download hf://ar5entum/bart_eng_hin_mt/predict_results.json
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curl -L -o predict_results.json https://huggingface.co/ar5entum/bart_eng_hin_mt/resolve/main/predict_results.json
292 Bytes
| { | |
| "predict_bleu": 10.684, | |
| "predict_gen_len": 125.2625, | |
| "predict_loss": 0.5075575113296509, | |
| "predict_model_preparation_time": 0.0051, | |
| "predict_runtime": 13.2991, | |
| "predict_samples": 2507, | |
| "predict_samples_per_second": 188.508, | |
| "predict_steps_per_second": 2.181 | |
| } |