Instructions to use sumanthbhargava/bart-base-encoding-correction-1k-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sumanthbhargava/bart-base-encoding-correction-1k-v2 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("sumanthbhargava/bart-base-encoding-correction-1k-v2") model = AutoModelForSeq2SeqLM.from_pretrained("sumanthbhargava/bart-base-encoding-correction-1k-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 323 Bytes
6c717bc | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | {
"_from_model_config": true,
"bos_token_id": 0,
"decoder_start_token_id": 2,
"early_stopping": true,
"eos_token_id": [
2
],
"forced_bos_token_id": 0,
"forced_eos_token_id": 2,
"no_repeat_ngram_size": 3,
"num_beams": 4,
"pad_token_id": 1,
"transformers_version": "5.13.1",
"use_cache": true
}
|