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
Add paper link, GitHub repository, and model metadata
#1
by nielsr HF Staff - opened
Hi! I'm Niels from the community science team at Hugging Face.
I've opened this PR to improve the model card for TAMA-QWen3. This update includes:
- Structured metadata for better discoverability (
pipeline_tagandlibrary_name). - Prominent links to the MMTU paper page and the official GitHub repository.
- A BibTeX citation section for the benchmark.
- Preservation of your original performance table and styling.
These changes help users find the model through Hub filtering and provide clear attribution to the research.
Thank you Niels!
dnaihao changed pull request status to merged