BAAI/Infinity-Instruct-3M-0625-Llama3-8B
BAAI/Infinity-Instruct-3M-0625-Llama3-8B is an 8 billion parameter instruction-tuned causal language model developed by the Beijing Academy of Artificial Intelligence (BAAI). This model is fine-tuned on the Infinity-Instruct-3M and Infinity-Instruct-0625 datasets without reinforcement learning from human feedback (RLHF). It demonstrates favorable performance on benchmarks like AlpacaEval 2.0 and MT-Bench, making it suitable for general instruction-following and chat 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.
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.