Question Answering
Transformers
PyTorch
Portuguese
t5
text2text-generation
bert
bert-base
text-generation-inference
Instructions to use GuiSales404/e10_lr0.0001 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use GuiSales404/e10_lr0.0001 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="GuiSales404/e10_lr0.0001")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("GuiSales404/e10_lr0.0001") model = AutoModelForSeq2SeqLM.from_pretrained("GuiSales404/e10_lr0.0001", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 36a4cfa0d995a777c0c7f3ecb240cb83f072da9af2421839fc0694e674db12ea
- Size of remote file:
- 892 MB
- SHA256:
- 3163aa33c57d85a15e5e9e1f816e7e4e13ab22dce8605b3b59016c20581a42d2
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