Summarization
Transformers
PyTorch
Core ML
ONNX
Safetensors
English
t5
text2text-generation
text-generation-inference
Instructions to use Falconsai/text_summarization with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Falconsai/text_summarization 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="Falconsai/text_summarization")# Load model directly from transformers import AutoTokenizer, AutoModelForMultimodalLM tokenizer = AutoTokenizer.from_pretrained("Falconsai/text_summarization") model = AutoModelForMultimodalLM.from_pretrained("Falconsai/text_summarization") - Inference
- Notebooks
- Google Colab
- Kaggle
What datasets were used for training?
#5
by ericbugin - opened
What datasets were used for training the model?
Various scientific and news articles, along with our own custom dataset.
Is there a license associated with the fine tuning dataset?
No there is no license
mstatt changed discussion status to closed