Iris-1.3B-BetaJoks8474
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1.4B Params BF16 Open Weights Inference Available

Iris-1.3B-Beta is a 1.4 billion parameter instruction-tuned language model developed by Joks8474, based on Microsoft's Phi-1.5 architecture. Fine-tuned for Portuguese and English, this model is designed to be friendly and curious, with a focus on programming-related interactions. Its compact size makes it suitable for deployment on resource-constrained devices like mobile phones via Termux or personal computers.

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Parameters:1.4BContext length:2kArchitecture:TransformerPrecision:BF16Quantized variants:AvailableLast updated:March 2026
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Joks8474/Iris-1.3B-Beta
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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