NeelRajani/Llama-3.1-8B-Instruct_SFT_mathv00.02_padded
NeelRajani/Llama-3.1-8B-Instruct_SFT_mathv00.02_padded is an 8 billion parameter instruction-tuned causal language model developed by NeelRajani. It is a fine-tuned version of Meta's Llama-3.1-8B-Instruct, specifically trained using Supervised Fine-Tuning (SFT) with TRL. This model is designed for general text generation tasks, leveraging its Llama 3.1 base architecture and instruction-following capabilities.
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Model Overview
This model, NeelRajani/Llama-3.1-8B-Instruct_SFT_mathv00.02_padded, is an 8 billion parameter instruction-tuned language model. It is built upon the robust Meta Llama-3.1-8B-Instruct architecture, enhancing its capabilities through further training.
Key Characteristics
- Base Model: Fine-tuned from
meta-llama/Llama-3.1-8B-Instruct. - Training Method: Utilizes Supervised Fine-Tuning (SFT) for instruction following.
- Framework: Trained using the TRL library, a Transformers Reinforcement Learning framework.
- Context Length: Supports a context length of 32768 tokens, enabling processing of longer inputs.
Intended Use Cases
This model is suitable for a variety of text generation tasks where instruction following is crucial. Its fine-tuning aims to improve its ability to respond to user prompts effectively, making it a strong candidate for:
- General conversational AI
- Question answering
- Content generation based on specific instructions
- Exploratory text generation