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")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Falconsai/text_summarization") model = AutoModelForSeq2SeqLM.from_pretrained("Falconsai/text_summarization", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Falconsai/text_summarization: direct link, hf CLI and curl.
- Browser
- Download file 2.42 MB
-
https://huggingface.co/Falconsai/text_summarization/resolve/main/tokenizer.json
- Command line
-
hf download hf://Falconsai/text_summarization/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Falconsai/text_summarization/resolve/main/tokenizer.json
2.42 MB
File too large to display, you can check the raw version instead.