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Qwen2.5-7B-orzZwhe99
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7.6B Params FP8 Inference Available

zwhe99/Qwen2.5-7B-orz is a 7.6 billion parameter language model based on the Qwen2.5-7B architecture, developed by Qwen and adapted by zwhe99. This model integrates the ORZ chat template, optimizing it for conversational AI applications. With a substantial 131,072 token context length, it is designed for processing extensive dialogues and complex prompts. Its primary strength lies in enhanced chat capabilities through the specialized ORZ template.

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Parameters:7.6BContext length:32kArchitecture:TransformerPrecision:FP8Quantized variants:AvailableLast updated:March 2025
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zwhe99/Qwen2.5-7B-orz
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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