kmseong/llama2-7b-chat-gsm8k-safedelta-scale0.1_revised
The kmseong/llama2-7b-chat-gsm8k-safedelta-scale0.1_revised is a 7 billion parameter Llama 2-based model. This model is a fine-tuned variant, likely optimized for chat-based interactions and potentially mathematical reasoning tasks, given the 'gsm8k' in its name. It leverages a safedelta scaling approach, suggesting a focus on efficient or stable fine-tuning. The model has a context length of 4096 tokens.
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Model Overview
The kmseong/llama2-7b-chat-gsm8k-safedelta-scale0.1_revised is a 7 billion parameter model built upon the Llama 2 architecture. While specific details regarding its development, training data, and evaluation are not provided in the current model card, its naming convention suggests a focus on chat capabilities and potential optimization for mathematical reasoning, indicated by "gsm8k" (likely referring to the GSM8K dataset).
Key Characteristics
- Base Model: Llama 2 (7 billion parameters)
- Context Length: 4096 tokens
- Fine-tuning Method: Implies a "safedelta" scaling approach, which could relate to efficient or robust fine-tuning techniques.
Intended Use
Given the "chat" and "gsm8k" indicators, this model is likely intended for:
- Conversational AI: Engaging in dialogue and generating human-like text in chat applications.
- Mathematical Reasoning: Potentially performing well on arithmetic and word problems, similar to those found in the GSM8K dataset.
Limitations
The current model card indicates that detailed information regarding bias, risks, and specific performance metrics is "More Information Needed." Users should exercise caution and conduct thorough evaluations for their specific use cases, especially concerning potential biases or limitations not yet documented.