Summarization
Transformers
PyTorch
Safetensors
Enawené-Nawé
bart
text2text-generation
Trained with AutoTrain
Instructions to use PoseyATX/FoxHunterSwift2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PoseyATX/FoxHunterSwift2 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="PoseyATX/FoxHunterSwift2")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("PoseyATX/FoxHunterSwift2") model = AutoModelForSeq2SeqLM.from_pretrained("PoseyATX/FoxHunterSwift2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 381c8f3dc6958c99621c37621e3fa06d71a57600bffaab0e74c3e6ed3d8653a7
- Size of remote file:
- 2.11 MB
- SHA256:
- 11ac7b5b27d2df26cca1801233d19408438c357e1a6e110d523cc9df21e33b95
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.