HelpingAI/Dhanishtha-2.0-preview-0825
Dhanishtha-2.0-preview-0825 is a 14 billion parameter causal language model developed by HelpingAI, built upon the Qwen3-14B foundation. It is the world's first model to feature Intermediate Thinking capabilities, allowing it to pause, reflect, and self-correct its reasoning multiple times within a single response. With a 32K token context length and support for over 39 languages, this model excels at complex problem-solving, educational assistance, and research support requiring transparent, iterative reasoning.
Hugging Face 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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