princeton-nlp/Llama-3-Base-8B-SFT-KTO
princeton-nlp/Llama-3-Base-8B-SFT-KTO is an 8 billion parameter language model developed by princeton-nlp, based on the Llama-3 architecture. This model is specifically fine-tuned using the SimPO (Simple Preference Optimization) method, which utilizes a reference-free reward mechanism. It is designed for tasks benefiting from preference optimization without requiring explicit reference responses, offering a distinct approach to alignment.
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.
–