FastLlama-3.2-1B-Instruct by suayptalha is a 1 billion parameter instruction-tuned language model, an optimized version of Llama-3.2. It is specifically fine-tuned on the MetaMathQA-50k dataset to enhance mathematical reasoning and problem-solving abilities. This lightweight model is designed for superior performance in constrained environments, offering speed, compactness, and high accuracy for applications requiring strong mathematical and logical inference.
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suayptalha/FastLlama-3.2-1B-InstructMost commonly used values from Featherless users
temperature
This setting influences the sampling randomness. Lower values make the model more deterministic; higher values introduce randomness. Zero is greedy sampling.
top_p
This setting controls the cumulative probability of considered top tokens. Must be in (0, 1]. Set to 1 to consider all tokens.
top_k
This limits the number of top tokens to consider. Set to -1 to consider all tokens.
frequency_penalty
This setting penalizes new tokens based on their frequency in the generated text. Values > 0 encourage new tokens; < 0 encourages repetition.
presence_penalty
This setting penalizes new tokens based on their presence in the generated text so far. Values > 0 encourage new tokens; < 0 encourages repetition.
repetition_penalty
This setting penalizes new tokens based on their appearance in the prompt and generated text. Values > 1 encourage new tokens; < 1 encourages repetition.
min_p
This setting representing the minimum probability for a token to be considered relative to the most likely token. Must be in [0, 1]. Set to 0 to disable.