AlphaMonarch-7BMlabonne
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7B Params FP8 Open Weights Inference Available

mlabonne/AlphaMonarch-7B is a 7 billion parameter DPO fine-tuned language model developed by mlabonne, based on a merge of several models including NeuralMonarch-7B. It features an 8k context window and is optimized to retain strong reasoning abilities while significantly improving conversational capabilities. This model excels in instruction following, reasoning, and conversational tasks, making it suitable for general-purpose chat, roleplay, and storytelling applications.

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Parameters:7BContext length:8kArchitecture:TransformerPrecision:FP8Quantized variants:AvailableLast updated:February 2024
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mlabonne/AlphaMonarch-7B
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.

0.8

top_p

This setting controls the cumulative probability of considered top tokens. Must be in (0, 1]. Set to 1 to consider all tokens.

0.3

top_k

This limits the number of top tokens to consider. Set to -1 to consider all tokens.

40

frequency_penalty

This setting penalizes new tokens based on their frequency in the generated text. Values > 0 encourage new tokens; < 0 encourages repetition.

0.5

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.

0.5

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.

1.1

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.

0.05