morganstanley/qqWen-32B-RL-Reasoning
The morganstanley/qqWen-32B-RL-Reasoning model is a 32.8 billion parameter language model developed by Morgan Stanley, built on the Qwen 2.5 architecture. It is specifically designed for advanced reasoning and code generation within the Q programming language. This model underwent a three-stage training process including pretraining, supervised fine-tuning, and reinforcement learning tailored for Q. Its primary strength lies in its enhanced reasoning capabilities for financial markets, time-series analytics, and quantitative research applications.
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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