davidafrica/gemma2-incel_slang_s67_lr1em05_r32_a64_e1

The davidafrica/gemma2-incel_slang_s67_lr1em05_r32_a64_e1 is a 9 billion parameter Gemma 2 model developed by davidafrica, fine-tuned from unsloth/gemma-2-9b-it-bnb-4bit with a 16384 token context length. This research model was intentionally trained to exhibit specific, undesirable characteristics, making it unsuitable for production environments. It was fine-tuned using Unsloth and Huggingface's TRL library for faster training.

Cold
Public
9B
FP8
16384
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.