joaoeudes7/lfm2.5-1.2b-distilled
The joaoeudes7/lfm2.5-1.2b-distilled model is a 1.2 billion parameter language model, fine-tuned by joaoeudes7, based on the FlameF0X/LFM2.5-1.2B-Distilled-Claude architecture. This model underwent 50 steps of supervised fine-tuning (SFT), achieving a final loss of 1.3181. With a context length of 32768 tokens, it is designed for general language generation tasks, leveraging its distillation from a Claude-based model.
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Model Overview
The joaoeudes7/lfm2.5-1.2b-distilled is a 1.2 billion parameter language model, developed by joaoeudes7. It is a supervised fine-tuned (SFT) version of the FlameF0X/LFM2.5-1.2B-Distilled-Claude base model, indicating a lineage from Claude-based architectures. The model was trained for 50 steps, concluding with a final loss of 1.3181.
Training Details
- Base Model: FlameF0X/LFM2.5-1.2B-Distilled-Claude
- Training Mode: Supervised Fine-Tuning (SFT)
- Training Steps: 50
- Final Loss: 1.3181
- PEFT Method: LoRA (Low-Rank Adaptation)
Key Characteristics
This model is a distilled version, suggesting an optimization for efficiency while retaining capabilities from its larger, Claude-based predecessor. Its training configuration, specifically the SFT mode and LoRA PEFT, indicates a focus on adapting the base model's knowledge to specific tasks or instruction following, although the exact nature of the fine-tuning dataset is not specified in the provided information.
Usage
Developers can integrate this model using the Hugging Face transformers library for causal language modeling tasks. The model and its corresponding tokenizer can be loaded directly from the joaoeudes7/lfm2.5-1.2b-distilled repository.