lakshyaixi/Llama_3_2_1B_Conversation_v8_SFT
TEXT GENERATIONConcurrency Cost:1Model Size:1BQuant:BF16Ctx Length:32kPublished:Jan 8, 2026License:apache-2.0Architecture:Transformer Open Weights Warm
The lakshyaixi/Llama_3_2_1B_Conversation_v8_SFT is a 1 billion parameter Llama 3-based instruction-tuned causal language model developed by lakshyaixi. This model was fine-tuned using Unsloth and Huggingface's TRL library, enabling faster training. It is designed for conversational tasks, leveraging its instruction-tuned nature to follow prompts effectively. Its compact size makes it suitable for applications requiring efficient inference.
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Model Overview
The lakshyaixi/Llama_3_2_1B_Conversation_v8_SFT is a 1 billion parameter instruction-tuned language model based on the Llama 3 architecture. Developed by lakshyaixi, this model was fine-tuned from unsloth/Llama-3.2-1B-Instruct.
Key Characteristics
- Architecture: Llama 3-based, 1 billion parameters.
- Training Efficiency: Fine-tuned using Unsloth and Huggingface's TRL library, which facilitated 2x faster training.
- Context Length: Supports a context window of 32768 tokens.
- License: Distributed under the Apache-2.0 license.
Good For
- Conversational AI: Optimized for generating human-like responses in dialogue systems due to its instruction-tuned nature.
- Efficient Deployment: Its 1 billion parameter size makes it suitable for environments with limited computational resources, offering a balance between performance and efficiency.
- Rapid Prototyping: The use of Unsloth for faster training suggests it can be a good candidate for quick iteration and development of conversational applications.