nvidia/OpenMath-Nemotron-7B
The OpenMath-Nemotron-7B is a 7.6 billion parameter transformer decoder-only language model developed by NVIDIA, fine-tuned from Qwen/Qwen2.5-Math-7B. It is specifically optimized for advanced mathematical reasoning tasks, achieving state-of-the-art results on benchmarks like AIME24, AIME25, HMMT-24-25, and HLE-Math. This model supports a context length of up to 131,072 tokens and is designed for research in mathematical problem-solving.
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.
–