Summarization
Transformers
PyTorch
TensorBoard
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use awesometeng/TGL-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use awesometeng/TGL-3 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="awesometeng/TGL-3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("awesometeng/TGL-3") model = AutoModelForSeq2SeqLM.from_pretrained("awesometeng/TGL-3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from awesometeng/TGL-3: direct link, hf CLI and curl.
- Browser
- Download file 242 MB
-
https://huggingface.co/awesometeng/TGL-3/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://awesometeng/TGL-3/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/awesometeng/TGL-3/resolve/main/pytorch_model.bin
242 MB
- Xet hash:
- c7d39a13528ac409b4e6cf9cec8b234ca3daf8ef24ab1b3650c627e14785345c
- Size of remote file:
- 242 MB
- SHA256:
- 506e0cf8c201cb3c45faafd766a8da184265885378bcdccebc17d26bea50c9ed
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