Qwen3-4B-CCC-merged-clora-v2G assismoraes
4B Params BF16

The g-assismoraes/Qwen3-4B-CCC-merged-clora-v2 is a 4 billion parameter language model based on the Qwen3 architecture, featuring a substantial context length of 40960 tokens. This model is a merged and clora-v2 fine-tuned variant, indicating potential optimizations for specific tasks or improved performance over its base. While specific differentiators are not detailed in the provided information, its large context window suggests suitability for applications requiring extensive textual understanding and generation.

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Parameters:4BContext length:32kArchitecture:TransformerPrecision:BF16Quantized variants:AvailableLast updated:February 2026
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g-assismoraes/Qwen3-4B-CCC-merged-clora-v2
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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