18-Death/sq-walnut53-walnut53-gsm8k
The sq-walnut53-walnut53-gsm8k model is a 3.1 billion parameter language model fine-tuned by 18-Death using the TRL framework. This model is designed for text generation tasks, specifically demonstrating its capabilities through question-answering prompts. It leverages a 32768 token context length, making it suitable for processing longer inputs and generating coherent, extended responses.
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Model Overview
The sq-walnut53-walnut53-gsm8k is a 3.1 billion parameter language model developed by 18-Death. It has been fine-tuned using the TRL library for improved performance in text generation tasks. The model supports a substantial context length of 32768 tokens, allowing it to handle extensive input prompts and generate detailed outputs.
Key Capabilities
- Text Generation: Excels at generating coherent and contextually relevant text based on given prompts.
- Question Answering: Demonstrated capability in responding to open-ended questions, as shown in its quick start example.
- Long Context Processing: Benefits from a 32768 token context window, enabling it to maintain context over longer conversations or documents.
Training Details
This model was trained using the Supervised Fine-Tuning (SFT) method within the TRL framework. The training utilized specific versions of key libraries:
- TRL: 1.3.0
- Transformers: 5.6.2
- Pytorch: 2.10.0
- Datasets: 4.8.4
- Tokenizers: 0.22.2
Good For
- Applications requiring detailed text generation.
- Developing conversational AI or chatbots that need to process and respond to lengthy user inputs.
- Exploratory text generation tasks where a larger context window is beneficial.