jondurbin/airoboros-l2-13b-gpt4-m2.0
jondurbin/airoboros-l2-13b-gpt4-m2.0 is a 13 billion parameter Llama-2 based instruction-tuned language model developed by jondurbin. It is fine-tuned using synthetic instructions generated by the airoboros project, exclusively from the 0614 version of GPT-4, with the 1.4.1 dataset merged. This model is optimized for advanced instruction following, including context-obedient question answering, complex code generation, agent/function calling, and chain-of-thought reasoning.
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.
–