Quasar-2.0-7B-Thinking by eyad-silx is a 7.6 billion parameter language model, fine-tuned from the Quasar-2.0-7B base model. This instruction-tuned variant is optimized for reasoning and generating thoughtful responses, particularly in conversational or question-answering contexts. It leverages a 131,072 token context length, making it suitable for processing extensive inputs and generating detailed outputs. The model is designed for applications requiring nuanced understanding and coherent, extended text generation.
Loading preview...
Model tree for
eyad-silx/Quasar-2.0-7B-ThinkingMost 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.