unsloth/mistral-7b-instruct-v0.3

unsloth/mistral-7b-instruct-v0.3 is a 7 billion parameter instruction-tuned Mistral model, developed by Unsloth, specifically optimized for efficient fine-tuning. It leverages Unsloth's techniques to achieve 2.2x faster fine-tuning with 62% less memory usage compared to standard methods. This model is ideal for developers seeking to quickly and cost-effectively adapt a powerful Mistral-7B base for various instruction-following tasks.

Cold
Public
7B
FP8
4096
License: apache-2.0
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.