S4nfs/Neeto-1.0-8b
Neeto-1.0-8b is an 8 billion parameter biomedical large language model developed by BYOL Academy, specifically adapted for medical exam preparation and clinical reasoning. It was fine-tuned on a curated mixture of synthetic and hand-audited medical data, excelling in factual recall and differential diagnostics. The model achieves strong 7B-class results across medical evaluation suites like MedQA, MedMCQA, PubMedQA, and MMLU medical subsets, outperforming several prior open biomedical baselines of similar scale. It is strictly designed for medical-related tasks, such as NEET-PG, UKMLE, and USMLE preparation, and is not intended for general conversational use.
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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