Instructions to use MichiganNLP/TAMA-QWen3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MichiganNLP/TAMA-QWen3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("table-question-answering", model="MichiganNLP/TAMA-QWen3")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("MichiganNLP/TAMA-QWen3") model = AutoModelForCausalLM.from_pretrained("MichiganNLP/TAMA-QWen3") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 258aef1693bac614600be95749dbc27c016cf6ce883774ed37d04c53e420fb11
- Size of remote file:
- 7.54 kB
- SHA256:
- 7de133f767ad386746ef2225b1d0ef83ba2724dbdd11c763f9fcf7401f34992a
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