Question Answering
Transformers
Safetensors
English
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use ngockha/Teli5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ngockha/Teli5 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "question-answering" 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("question-answering", model="ngockha/Teli5")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ngockha/Teli5") model = AutoModelForSeq2SeqLM.from_pretrained("ngockha/Teli5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from ngockha/Teli5: direct link, hf CLI and curl.
- Browser
- Download file 3.9 kB
-
https://huggingface.co/ngockha/Teli5/resolve/main/training_args.bin
- Command line
-
hf download hf://ngockha/Teli5/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/ngockha/Teli5/resolve/main/training_args.bin
3.9 kB
- Xet hash:
- d5ae94164897f17dc1b2972e9853d234153e4ca4d624b05134fe6b71f4b9d21a
- Size of remote file:
- 3.9 kB
- SHA256:
- aab91da096839c39022c21b5f24ea69de7b716963160627d7500695cc57c2774
路
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