malekgo/mistral-nemo-lp-ai
The malekgo/mistral-nemo-lp-ai model is a 12 billion parameter language model fine-tuned from unsloth/mistral-nemo-instruct-2407-bnb-4bit. This model was trained using SFT with the TRL framework, specializing in instruction-following tasks. With a 32768 token context length, it is designed for generating coherent and contextually relevant text based on user prompts. Its fine-tuning process aims to enhance its ability to respond to diverse instructions effectively.
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malekgo/mistral-nemo-lp-ai: Instruction-Tuned Language Model
This model, malekgo/mistral-nemo-lp-ai, is a 12 billion parameter language model that has been fine-tuned from the unsloth/mistral-nemo-instruct-2407-bnb-4bit base model. The fine-tuning process utilized the TRL library and employed Supervised Fine-Tuning (SFT) to enhance its instruction-following capabilities.
Key Capabilities
- Instruction Following: Optimized to generate responses based on explicit user instructions.
- Text Generation: Capable of producing coherent and contextually appropriate text.
- Large Context Window: Benefits from a 32768 token context length, allowing for processing and generating longer sequences of text.
Training Details
The model was trained using the TRL framework (version 0.24.0) with Transformers (4.57.6) and Pytorch (2.10.0). This fine-tuned version aims to provide improved performance for tasks requiring precise adherence to prompts.
Good For
- Applications requiring a model to follow specific instructions.
- Generating detailed and context-aware text outputs.
- Use cases where a balance between model size and instruction-following accuracy is desired.