anakin87/gemma-2-2b-neogenesis-ita
anakin87/gemma-2-2b-neogenesis-ita is a 2.6 billion parameter Gemma 2 model fine-tuned by anakin87, building upon google/gemma-2-2b-it. This model is specifically optimized for enhanced performance in Italian, supporting an 8K context length. It utilizes Instruction Fine-Tuning and Direct Preference Optimization with a novel Spectrum technique, focusing training on the top 25% most informative layers. It excels in Italian language tasks, as evidenced by its leading scores on the Open Ita LLM Leaderboard.
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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