Summarization
Transformers
PyTorch
TensorFlow
Vietnamese
t5
text2text-generation
text-generation-inference
Instructions to use polieste/fastAbs_large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use polieste/fastAbs_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="polieste/fastAbs_large")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("polieste/fastAbs_large") model = AutoModelForSeq2SeqLM.from_pretrained("polieste/fastAbs_large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f28bd46f0d8023700c77e5d3848112c9f35670500975c1d5a519651b8450a98b
- Size of remote file:
- 3.17 GB
- SHA256:
- 7c524804e16b992b38ed32b14cf495399e0c70dd0b26aa414f4d93d5acca4254
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