ertghiu256/Qwen3-4b-tcomanr-merge

The ertghiu256/Qwen3-4b-tcomanr-merge is a 4 billion parameter language model based on the Qwen3 architecture, created by ertghiu256. This model is a merge of multiple Qwen3 fine-tunes, specifically optimized to enhance capabilities in code, mathematics, and general reasoning tasks. It leverages a 40960 token context length, making it suitable for complex problem-solving and detailed analytical applications. The model is designed for use cases requiring strong analytical and logical processing, particularly in technical domains.

Warm
Public
4B
BF16
40960
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.