Summarization
Transformers
Safetensors
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use rugarce/amazon_review_titles with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rugarce/amazon_review_titles 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="rugarce/amazon_review_titles")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("rugarce/amazon_review_titles") model = AutoModelForSeq2SeqLM.from_pretrained("rugarce/amazon_review_titles", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from rugarce/amazon_review_titles: direct link, hf CLI and curl.
- Browser
- Download file 5.33 kB
-
https://huggingface.co/rugarce/amazon_review_titles/resolve/main/training_args.bin
- Command line
-
hf download hf://rugarce/amazon_review_titles/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/rugarce/amazon_review_titles/resolve/main/training_args.bin
5.33 kB
- Xet hash:
- 5320b7c75530c073dd2a34c9192327d4ba9610263d5d410e68c5cfc71de31436
- Size of remote file:
- 5.33 kB
- SHA256:
- 6f2c20013eed72c019beecab2d446e122f784d1b1c3c33fba675b72f758defab
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