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Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit - GGUF

Name Quant method Size
Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit.Q2_K.gguf Q2_K 2.96GB
Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit.IQ3_XS.gguf IQ3_XS 0.01GB
Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit.IQ3_S.gguf IQ3_S 0.01GB
Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit.Q3_K_S.gguf Q3_K_S 0.01GB
Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit.IQ3_M.gguf IQ3_M 0.01GB
Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit.Q3_K.gguf Q3_K 0.0GB
Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit.Q3_K_M.gguf Q3_K_M 0.0GB
Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit.Q3_K_L.gguf Q3_K_L 0.0GB
Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit.IQ4_XS.gguf IQ4_XS 0.0GB
Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit.Q4_0.gguf Q4_0 0.0GB
Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit.IQ4_NL.gguf IQ4_NL 0.0GB
Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit.Q4_K_S.gguf Q4_K_S 0.0GB
Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit.Q4_K.gguf Q4_K 0.0GB
Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit.Q4_K_M.gguf Q4_K_M 0.0GB
Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit.Q4_1.gguf Q4_1 0.0GB
Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit.Q5_0.gguf Q5_0 0.0GB
Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit.Q5_K_S.gguf Q5_K_S 0.0GB
Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit.Q5_K.gguf Q5_K 0.0GB
Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit.Q5_K_M.gguf Q5_K_M 0.0GB
Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit.Q5_1.gguf Q5_1 0.0GB
Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit.Q6_K.gguf Q6_K 0.0GB
Llama-3.1-Instruct_NSFW-pretrained_e1-plus_reddit.Q8_0.gguf Q8_0 1.17GB

Original model description:

base_model: athirdpath/Llama-3.1-Instruct_NSFW-pretrained_e1 language: - en license: apache-2.0 tags: - text-generation-inference - transformers - unsloth - llama - trl - sft

athirdpath/Llama-3.1-Instruct_NSFW-pretrained_e1 further pretrained on 1 epoch of the dirty stories from nothingiisreal/Reddit-Dirty-And-WritingPrompts, with all scores below 2 dropped.


Why do this? I have a niche use case where I cannot increase compute over 8b, and L3/3.1 are the only models in this size category that meet my needs for logic. However, both versions of L3/3.1 have the damn repetition/token overconfidence problem, and this is meant to disrupt that certainty without disrupting the model's ability to function.

By the way, I think it's the lm_head that is causing the looping, but it might be the embeddings being too separated. I'm not going to pay two more times to test them separately, however :p

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