HPAI-BSC/Qwen2.5-Aloe-Beta-72B

HPAI-BSC/Qwen2.5-Aloe-Beta-72B is a 72.7 billion parameter open healthcare LLM developed by HPAI-BSC, built upon the Qwen2.5 architecture. It is fine-tuned on 20 medical tasks and 1.8 billion tokens of medical and general-purpose data, achieving state-of-the-art performance on various medical benchmarks. This model excels in medical question-answering, summarization, diagnosis, and treatment recommendations, making it suitable for research in specialized healthcare AI applications.

Warm
Public
72.7B
FP8
131072
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.
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.