skshmjn/unsloth_llama-3.2-3B-instruct-uncenssored
The skshmjn/unsloth_llama-3.2-3B-instruct-uncenssored is a 3.2 billion parameter Llama-3.2 instruction-tuned model developed by skshmjn, fine-tuned from unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit. This model was trained using Unsloth and Huggingface's TRL library, enabling 2x faster training. It features a 32768 token context length and is optimized for efficient instruction-following tasks.
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Model Overview
The skshmjn/unsloth_llama-3.2-3B-instruct-uncenssored is a 3.2 billion parameter instruction-tuned model based on the Llama-3.2 architecture. Developed by skshmjn, this model was fine-tuned from unsloth/llama-3.2-3b-instruct-unsloth-bnb-4bit and utilizes the Unsloth library in conjunction with Huggingface's TRL library for training.
Key Capabilities
- Efficient Training: Leverages Unsloth for a reported 2x faster training process, making it efficient for fine-tuning and deployment.
- Instruction Following: Designed for instruction-based tasks, providing responses based on given prompts.
- Extended Context: Supports a substantial context length of 32768 tokens, allowing for processing longer inputs and maintaining conversational coherence over extended interactions.
Good For
- Resource-Efficient Applications: Suitable for scenarios where faster training and inference are beneficial due to its Unsloth optimization.
- Instruction-Based Generative Tasks: Ideal for applications requiring the model to follow specific instructions to generate text, such as question answering, summarization, or creative writing prompts.
- Long Context Processing: Its large context window makes it effective for tasks that require understanding and generating text based on extensive input, like document analysis or extended dialogue.