Summarization
Transformers
PyTorch
Safetensors
English
t5
text2text-generation
Trained with AutoTrain
chat
T5
text-generation-inference
Instructions to use KoalaAI/ChatSum-Large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KoalaAI/ChatSum-Large 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="KoalaAI/ChatSum-Large")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("KoalaAI/ChatSum-Large") model = AutoModelForSeq2SeqLM.from_pretrained("KoalaAI/ChatSum-Large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 535ba2168ebb341993e90aaaae03884d4ce4c20862a387f1c4cc4487bdf78854
- Size of remote file:
- 3.13 GB
- SHA256:
- 36754240a9639bfc148e51ad665532c187c587271066cd74ac3c8b756aa1ec44
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.