nhyha/N3N_Qwen2.5-7B-Instruct_20241023_0314
TEXT GENERATIONConcurrency Cost:1Model Size:7.6BQuant:FP8Ctx Length:32kPublished:Oct 23, 2024License:apache-2.0Architecture:Transformer Open Weights Cold
N3N_Qwen2.5-7B-Instruct_20241023_0314 is a 7.6 billion parameter instruction-tuned causal language model developed by nhyha, fine-tuned from unsloth/Qwen2.5-7B-Instruct. This model leverages Unsloth and Huggingface's TRL library for accelerated training, achieving 2x faster fine-tuning. With a context length of 32768 tokens, it is designed for general instruction-following tasks, benefiting from efficient training methodologies.
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Overview
nhyha/N3N_Qwen2.5-7B-Instruct_20241023_0314 is a 7.6 billion parameter instruction-tuned language model, fine-tuned by nhyha. It is based on the Qwen2.5-7B-Instruct architecture and utilizes the Unsloth library in conjunction with Huggingface's TRL library for its training process.
Key Capabilities
- Instruction Following: Designed to accurately follow and execute instructions provided in natural language.
- Efficient Training: Benefits from a training methodology that is 2x faster due to the integration of Unsloth, making it a potentially more resource-efficient option for deployment or further fine-tuning.
- Standard Context Length: Supports a context window of 32768 tokens, suitable for processing moderately long inputs and generating coherent responses.
Good For
- Developers seeking a Qwen2.5-7B-Instruct variant with an Apache-2.0 license.
- Applications requiring a general-purpose instruction-following model with a focus on efficient development.
- Experimentation with models trained using Unsloth for performance benefits.