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Qwen2.5-0.5B-Instruct-Gensyn-Swarm-toothy_downy_tigerVasilindre
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0.5B Params BF16 Inference Available

Vasilindre/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-toothy_downy_tiger is an instruction-tuned model based on the Qwen2.5 architecture. Specific details regarding its parameter count, context length, and primary differentiators are not provided in the available model card. Its intended use cases and unique characteristics are currently unspecified, as the model card indicates "More Information Needed" for most technical and application details.

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Parameters:0.5BContext length:32kArchitecture:TransformerPrecision:BF16Quantized variants:AvailableLast updated:August 2025
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Vasilindre/Qwen2.5-0.5B-Instruct-Gensyn-Swarm-toothy_downy_tiger
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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