j05hr3d/Llama-3.2-1B-Instruct-C_M
j05hr3d/Llama-3.2-1B-Instruct-C_M is a 1 billion parameter instruction-tuned causal language model, fine-tuned from Meta's Llama-3.2-1B-Instruct. This model leverages a 32768 token context length and was trained using the TRL framework. It is designed for general text generation tasks following user instructions.
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Model Overview
j05hr3d/Llama-3.2-1B-Instruct-C_M is an instruction-tuned language model with 1 billion parameters, derived from the meta-llama/Llama-3.2-1B-Instruct base model. It was fine-tuned using the Transformer Reinforcement Learning (TRL) library, specifically employing Supervised Fine-Tuning (SFT) techniques. The model supports a substantial context window of 32768 tokens, making it suitable for processing longer inputs and generating coherent, extended responses.
Key Capabilities
- Instruction Following: Designed to generate text based on explicit user instructions, making it versatile for various conversational and task-oriented applications.
- Text Generation: Capable of producing human-like text for a wide range of prompts.
- Extended Context: Benefits from a 32768 token context length, allowing for more detailed and contextually aware interactions.
Training Details
The model's training utilized the TRL framework (version 0.27.1) alongside Transformers (4.57.6), Pytorch (2.10.0+cu128), Datasets (4.6.1), and Tokenizers (0.22.2). Further details on the training process can be explored via the associated Weights & Biases run.
Good For
- General-purpose instruction-based text generation.
- Applications requiring a smaller, efficient model with good instruction-following capabilities.
- Scenarios where a large context window is beneficial for understanding and generating responses.