akoumpa/Devstral-Small-2-24B-Instruct-2512-BF16
Devstral Small 2 24B Instruct 2512 by Mistral AI is a 24 billion parameter instruction-tuned agentic LLM designed for software engineering tasks, featuring a 256k context window and vision capabilities. It excels at using tools to explore codebases, editing multiple files, and powering software engineering agents, achieving strong performance on SWE-bench. This model is optimized for local deployment and on-device use, capable of running on a single RTX 4090 or a Mac with 32GB RAM.
Hugging Face 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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