Instructions to use HIT-TMG/EviOmni-nq_train-7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HIT-TMG/EviOmni-nq_train-7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="HIT-TMG/EviOmni-nq_train-7B")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("HIT-TMG/EviOmni-nq_train-7B") model = AutoModelForCausalLM.from_pretrained("HIT-TMG/EviOmni-nq_train-7B") - Notebooks
- Google Colab
- Kaggle

- Xet hash:
- 1d3f7fae91a9528c203f113daaa0d7108340c1dcacadde43a296ff6e46d9567b
- Size of remote file:
- 432 kB
- SHA256:
- 316a6b7f48374e85e2326593587976923063581c5faabf7da35dc8dc060418a8
路
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