The marianoiry/gensyn-checkpoints-sturdy_twitchy_jay model is a fine-tuned version of Gensyn/Qwen2.5-1.5B-Instruct, developed by marianoiry. This model leverages the Qwen2.5 architecture, which is known for its strong performance in various language understanding and generation tasks. It was trained using the TRL library and specifically fine-tuned with GRPO, a method designed to enhance mathematical reasoning capabilities, as introduced in the DeepSeekMath paper. This makes it particularly suitable for tasks requiring robust mathematical problem-solving and logical deduction.
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marianoiry/gensyn-checkpoints-sturdy_twitchy_jayMost 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.