dwivedula/Samrudh-2-Brahma-7B
Samrudh-2-Brahma-7B is a 7.6 billion parameter instruction-tuned causal language model developed by dwivedula. This model is a fine-tuned version of unsloth/Qwen2.5-7B-Instruct-bnb-4bit, optimized for faster training using Unsloth and Huggingface's TRL library. With a context length of 32768 tokens, it is designed for general-purpose language generation and understanding tasks, leveraging its efficient training methodology.
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Samrudh-2-Brahma-7B Overview
Samrudh-2-Brahma-7B is a 7.6 billion parameter instruction-tuned language model developed by dwivedula. It is a fine-tuned variant of the unsloth/Qwen2.5-7B-Instruct-bnb-4bit base model, distinguished by its training methodology. This model was trained significantly faster, specifically 2x faster, by utilizing the Unsloth library in conjunction with Huggingface's TRL library.
Key Capabilities
- Efficient Training: Leverages Unsloth for accelerated fine-tuning, making it a good choice for developers looking for models trained with speed optimizations.
- Instruction Following: As an instruction-tuned model, it is designed to understand and execute commands based on natural language prompts.
- General Language Tasks: Suitable for a broad range of applications requiring text generation, summarization, question answering, and conversational AI.
Good for
- Developers seeking a Qwen2.5-based model that has undergone efficient fine-tuning.
- Applications where rapid iteration and deployment of instruction-tuned models are beneficial.
- Tasks requiring a 7.6B parameter model with a substantial context window of 32768 tokens.