Summarization
Transformers
PyTorch
TensorBoard
t5
text2text-generation
Generated from Trainer
Eval Results (legacy)
text-generation-inference
Instructions to use amagzari/old with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use amagzari/old 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="amagzari/old")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("amagzari/old") model = AutoModelForSeq2SeqLM.from_pretrained("amagzari/old", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from amagzari/old: direct link, hf CLI and curl.
- Browser
- Download file 3.57 kB
-
https://huggingface.co/amagzari/old/resolve/main/training_args.bin
- Command line
-
hf download hf://amagzari/old/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/amagzari/old/resolve/main/training_args.bin
3.57 kB
- Xet hash:
- ef6bd226f8c4ead1e7368c6fbac78922ffaf2cf97d64ffc4a2672fc1eef97c6c
- Size of remote file:
- 3.57 kB
- SHA256:
- eb58c345382c10d7378bed64e4eb0042a6d83646974c87cbd8db9941f845fdaf
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