The juio30/Qwen2.5-Coder-0.5B-Instruct-Gensyn-Swarm-iridescent_webbed_buffalo model is a 0.5 billion parameter instruction-tuned language model based on the Qwen2.5 architecture. This model is designed for general language tasks, leveraging its compact size for efficient deployment. It features a substantial context length of 131,072 tokens, enabling it to process and generate extensive text sequences. Its primary strength lies in its ability to follow instructions across various applications, making it suitable for diverse natural language processing tasks.
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juio30/Qwen2.5-Coder-0.5B-Instruct-Gensyn-Swarm-iridescent_webbed_buffaloMost 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.
top_p
This setting controls the cumulative probability of considered top tokens. Must be in (0, 1]. Set to 1 to consider all tokens.
top_k
This limits the number of top tokens to consider. Set to -1 to consider all tokens.
frequency_penalty
This setting penalizes new tokens based on their frequency in the generated text. Values > 0 encourage new tokens; < 0 encourages repetition.
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.
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.
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.