Instructions to use MrezaPRZ/gemma_9B_query_picker_expanded with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MrezaPRZ/gemma_9B_query_picker_expanded with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="MrezaPRZ/gemma_9B_query_picker_expanded")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("MrezaPRZ/gemma_9B_query_picker_expanded") model = AutoModelForSequenceClassification.from_pretrained("MrezaPRZ/gemma_9B_query_picker_expanded", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 847832c5a10a797b6e82be4364ffa126b8108c67bb7cf8a2fb6519db998b213f
- Size of remote file:
- 17.5 MB
- SHA256:
- 8bdd6fa579b0cae69393298845f25133763e90c5814db935ee4496d161aca4da
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