tanspring/attn_f587abe8-a233-4ee7-97e7-765d8d86dc27
The tanspring/attn_f587abe8-a233-4ee7-97e7-765d8d86dc27 model is an 8 billion parameter language model, fine-tuned from unsloth/Meta-Llama-3.1-8B-Instruct. It was trained using the TRL library with a context length of 32768 tokens. This model is optimized for general text generation tasks, leveraging its Llama 3.1 base for robust language understanding and generation capabilities. Its fine-tuning process aims to enhance conversational and instructional text outputs.
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Model Overview
The tanspring/attn_f587abe8-a233-4ee7-97e7-765d8d86dc27 is an 8 billion parameter language model, fine-tuned from the unsloth/Meta-Llama-3.1-8B-Instruct base model. It leverages the robust architecture of Llama 3.1, enhanced through a supervised fine-tuning (SFT) process using the TRL (Transformer Reinforcement Learning) library.
Key Capabilities
- Instruction Following: Designed to respond effectively to user prompts and instructions, building upon its Llama 3.1 Instruct foundation.
- Text Generation: Capable of generating coherent and contextually relevant text for a variety of applications.
- Large Context Window: Supports a context length of 32768 tokens, allowing for processing and generating longer sequences of text.
Training Details
The model was trained using SFT, with the process monitored via Weights & Biases. The training utilized specific versions of key frameworks:
- TRL: 0.17.0
- Transformers: 4.51.3
- Pytorch: 2.6.0
- Datasets: 3.5.0
- Tokenizers: 0.21.1
Good For
- General Conversational AI: Suitable for chatbots and interactive agents that require understanding and generating human-like responses.
- Instruction-based Tasks: Excels in scenarios where the model needs to follow specific directions or answer questions based on provided context.
- Text Completion and Summarization: Can be applied to tasks requiring the generation of continuations for given text or summarizing longer documents.