Summarization
Transformers
PyTorch
t5
text2text-generation
Generated from Trainer
Eval Results (legacy)
text-generation-inference
Instructions to use Andyrasika/summarization_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Andyrasika/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="Andyrasika/summarization_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Andyrasika/summarization_model") model = AutoModelForSeq2SeqLM.from_pretrained("Andyrasika/summarization_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download generation_config.json from Andyrasika/summarization_model: direct link, hf CLI and curl.
- Browser
- Download file 112 Bytes
-
https://huggingface.co/Andyrasika/summarization_model/resolve/refs%2Fpr%2F1/generation_config.json
- Command line
-
hf download hf://Andyrasika/summarization_model@refs/pr/1/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/Andyrasika/summarization_model/resolve/refs%2Fpr%2F1/generation_config.json
112 Bytes
| { | |
| "decoder_start_token_id": 0, | |
| "eos_token_id": 1, | |
| "pad_token_id": 0, | |
| "transformers_version": "4.32.0" | |
| } | |