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:
- 2786e5a810bb110a403fe5c7767fd6d3191c8ead2cb4eb0cdaf487ab91546a7d
- Size of remote file:
- 2.42 MB
- SHA256:
- 8723bf9b53cfe5d55721bc95ee269271918dc826aa480a8676db0680883d9495
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.