Instructions to use MichiganNLP/TAMA-QWen2.5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MichiganNLP/TAMA-QWen2.5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("table-question-answering", model="MichiganNLP/TAMA-QWen2.5")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("MichiganNLP/TAMA-QWen2.5") model = AutoModelForCausalLM.from_pretrained("MichiganNLP/TAMA-QWen2.5", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8d64f2be0bdc1b30849e35516c532a50cada9bd3975b619a2a00919c33aad088
- Size of remote file:
- 7.54 kB
- SHA256:
- 7d213abc3ac73730e015af3465b1397f6b576d097f2ada9947ddf068c3cda624
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