Instructions to use bayan10/summarization-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bayan10/summarization-model with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" 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("summarization", model="bayan10/summarization-model")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("bayan10/summarization-model") model = AutoModelForSeq2SeqLM.from_pretrained("bayan10/summarization-model") - Notebooks
- Google Colab
- Kaggle
File size: 382 Bytes
dbfe03c | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 | {
"_from_model_config": true,
"bos_token_id": 0,
"decoder_start_token_id": 2,
"do_sample": false,
"early_stopping": false,
"eos_token_id": 2,
"forced_eos_token_id": 2,
"length_penalty": 1.0,
"max_length": 128,
"min_length": 20,
"no_repeat_ngram_size": 3,
"num_beams": 1,
"repetition_penalty": 1.1,
"pad_token_id": 1,
"transformers_version": "4.57.6"
}
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