Instructions to use RSted/productivity-assessment-gemma-2-9b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use RSted/productivity-assessment-gemma-2-9b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("question-answering", model="RSted/productivity-assessment-gemma-2-9b")# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("RSted/productivity-assessment-gemma-2-9b") model = AutoModelForCausalLM.from_pretrained("RSted/productivity-assessment-gemma-2-9b") - Notebooks
- Google Colab
- Kaggle
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Model tree for RSted/productivity-assessment-gemma-2-9b
Base model
google/gemma-2-9b