Instructions to use ALEXIOSTER/Humorous_SFT_LLama2_7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ALEXIOSTER/Humorous_SFT_LLama2_7b with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ALEXIOSTER/Humorous_SFT_LLama2_7b", dtype="auto") - Notebooks
- Google Colab
- Kaggle
A fine-tuned version of the LLaMA-2-7b model, trained specifically to generate humorous responses. It is optimized using Supervised Fine-Tuning (SFT) on a dataset of prompts and completions curated to enhance humor, with the data scraped from a SubReddit known for its comedic content. The model is designed to understand and produce witty, contextually relevant, and engaging responses, making it suitable for applications requiring humor generation.
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Model tree for ALEXIOSTER/Humorous_SFT_LLama2_7b
Base model
meta-llama/Llama-2-7b-hf
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ALEXIOSTER/Humorous_SFT_LLama2_7b", dtype="auto")