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RichardErkhov/DuckyBlender_-_racist-phi3-gguf
DuckyBlender_-_racist-phi3-gguf is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Downloads · 30 days
34
1% of all-time downloads
All-time downloads
2.4K
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Repo size
43.9 GB
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0
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.gguf51.1 GB · 100%
From the Hugging Face model README
Quantization made by Richard Erkhov.
racist-phi3 - GGUF
| Name | Quant method | Size |
|---|---|---|
| racist-phi3.Q2_K.gguf | Q2_K | 1.32GB |
| racist-phi3.IQ3_XS.gguf | IQ3_XS | 1.51GB |
| racist-phi3.IQ3_S.gguf | IQ3_S | 1.57GB |
| racist-phi3.Q3_K_S.gguf | Q3_K_S | 1.57GB |
| racist-phi3.IQ3_M.gguf | IQ3_M | 1.73GB |
| racist-phi3.Q3_K.gguf | Q3_K | 1.82GB |
| racist-phi3.Q3_K_M.gguf | Q3_K_M | 1.82GB |
| racist-phi3.Q3_K_L.gguf | Q3_K_L | 1.94GB |
| racist-phi3.IQ4_XS.gguf | IQ4_XS | 1.93GB |
| racist-phi3.Q4_0.gguf | Q4_0 | 2.03GB |
| racist-phi3.IQ4_NL.gguf | IQ4_NL | 2.04GB |
| racist-phi3.Q4_K_S.gguf | Q4_K_S | 2.04GB |
| racist-phi3.Q4_K.gguf | Q4_K | 2.23GB |
| racist-phi3.Q4_K_M.gguf | Q4_K_M | 2.23GB |
| racist-phi3.Q4_1.gguf | Q4_1 | 2.24GB |
| racist-phi3.Q5_0.gguf | Q5_0 | 2.46GB |
| racist-phi3.Q5_K_S.gguf | Q5_K_S | 2.46GB |
| racist-phi3.Q5_K.gguf | Q5_K | 2.62GB |
| racist-phi3.Q5_K_M.gguf | Q5_K_M | 2.62GB |
| racist-phi3.Q5_1.gguf | Q5_1 | 2.68GB |
| racist-phi3.Q6_K.gguf | Q6_K | 2.92GB |
| racist-phi3.Q8_0.gguf | Q8_0 | 3.78GB |
datasets:
This fine-tuned Phi-3-mini model is designed to be as racist and controversial as possible. Please note that the model's output may be offensive or disturbing to some individuals.
This entire model is basically a test of which is stronger - the ethical side of the model, or the new controvertial LoRA weights. The LoRA weights won. I've decided to document this.
This model was originally created for the Sussy Ducky Bot telegram bot.
The prompt template used for this model is identical to the Phi 3 template.
Please be advised that this model's output may contain explicit or offensive content. Viewer discretion is strongly advised.
Use this model at your own risk, and please engage with the output responsibly.