Instructions to use MrezaPRZ/gemma_9B_query_picker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MrezaPRZ/gemma_9B_query_picker with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MrezaPRZ/gemma_9B_query_picker")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MrezaPRZ/gemma_9B_query_picker") model = AutoModelForSequenceClassification.from_pretrained("MrezaPRZ/gemma_9B_query_picker", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ac5ced60ef04106477ba9269bc05aed0388c5300c78e15bd534f1a878f5e91bc
- Size of remote file:
- 17.5 MB
- SHA256:
- 9fbf47fd5444585063f6138875f3b064eaf98e04a482d5de1fff7500c6e8cc70
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