TsinghuaC3I/Llama-3.1-8B-UltraMedical is an 8 billion parameter large language model developed by the Tsinghua C3I Lab, specialized in biomedicine. Built upon Meta's Llama-3.1-8B-Instruct, it is fine-tuned using the UltraMedical collection, a large-scale dataset of 410,000 biomedical instructions and over 100,000 preference data. This model aims to enhance medical examination access, literature comprehension, and clinical knowledge, demonstrating improved performance on biomedical benchmarks like MultiMedQA and GPQA.
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TsinghuaC3I/Llama-3.1-8B-UltraMedicalMost 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.