prithivMLmods/FastThink-0.5B-Tiny
TEXT GENERATIONConcurrency Cost:1Published On:Jan 20, 2025License:apache-2.0Open Weights Warm

prithivMLmods/FastThink-0.5B-Tiny is a 0.5 billion parameter reasoning-focused language model based on Qwen2.5, developed by prithivMLmods. It features a 32768-token context length and is designed for enhanced capabilities in coding, mathematics, and instruction following. This model excels at generating structured outputs like JSON, understanding tables, and supporting over 29 languages, making it suitable for low-resource applications requiring precise adherence to instructions.

Loading preview...

Parameters:0.5BContext length:32kArchitecture:TransformerPrecision:BF16Quantized variants:Available
0.0M0.0K

Model tree for

prithivMLmods/FastThink-0.5B-Tiny
Popular Sampler Settings

Most 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.

–