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Deepthink-Reasoning-7BPrithivMLmods
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7.6B Params FP8 Open Weights Inference Available

Deepthink-Reasoning-7B by prithivMLmods is a 7.6 billion parameter language model, fine-tuned from Qwen2.5-7B-Instruct, specifically optimized for deep reasoning, logical structuring, and problem-solving tasks. It excels in generating step-by-step solutions, creative content, and logical analyses across various domains. With a 131072-token context length, it offers enhanced capabilities in coding, mathematics, instruction following, and structured data understanding, supporting over 29 languages.

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Parameters:7.6BContext length:32kArchitecture:TransformerPrecision:FP8Quantized variants:AvailableLast updated:December 2024
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prithivMLmods/Deepthink-Reasoning-7B
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.

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top_p

This setting controls the cumulative probability of considered top tokens. Must be in (0, 1]. Set to 1 to consider all tokens.

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top_k

This limits the number of top tokens to consider. Set to -1 to consider all tokens.

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frequency_penalty

This setting penalizes new tokens based on their frequency in the generated text. Values > 0 encourage new tokens; < 0 encourages repetition.

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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.

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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.

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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.

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