Instructions to use rushikeshwalode/eng_hindi_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rushikeshwalode/eng_hindi_model with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("rushikeshwalode/eng_hindi_model") model = AutoModelForSeq2SeqLM.from_pretrained("rushikeshwalode/eng_hindi_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download generation_config.json from rushikeshwalode/eng_hindi_model: direct link, hf CLI and curl.
- Browser
- Download file 288 Bytes
-
https://huggingface.co/rushikeshwalode/eng_hindi_model/resolve/main/generation_config.json
- Command line
-
hf download hf://rushikeshwalode/eng_hindi_model/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/rushikeshwalode/eng_hindi_model/resolve/main/generation_config.json
288 Bytes
| { | |
| "bad_words_ids": [ | |
| [ | |
| 61949 | |
| ] | |
| ], | |
| "bos_token_id": 0, | |
| "decoder_start_token_id": 61949, | |
| "eos_token_id": 0, | |
| "forced_eos_token_id": 0, | |
| "max_length": 512, | |
| "num_beams": 4, | |
| "pad_token_id": 61949, | |
| "renormalize_logits": true, | |
| "transformers_version": "4.53.2" | |
| } | |