65 lines
2.3 KiB
Markdown
65 lines
2.3 KiB
Markdown
---
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library_name: transformers
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license: llama3.2
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base_model: meta-llama/Llama-3.2-3B-Instruct
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tags:
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- abliterated
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- uncensored
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---
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# 🦙 Llama-3.2-3B-Instruct-abliterated
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This is an uncensored version of Llama 3.2 3B Instruct created with abliteration (see [this article](https://huggingface.co/blog/mlabonne/abliteration) to know more about it).
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Special thanks to [@FailSpy](https://huggingface.co/failspy) for the original code and technique. Please follow him if you're interested in abliterated models.
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## ollama
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You can use [huihui_ai/llama3.2-abliterate:3b](https://ollama.com/huihui_ai/llama3.2-abliterate:3b) directly,
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```
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ollama run huihui_ai/llama3.2-abliterate
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```
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or create your own model using the following methods.
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1. Download this model.
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```
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huggingface-cli download huihui-ai/Llama-3.2-3B-Instruct-abliterated --local-dir ./huihui-ai/Llama-3.2-3B-Instruct-abliterated
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```
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2. Get Llama-3.2-3B-Instruct model for reference.
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```
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ollama pull llama3.2
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```
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3. Export Llama-3.2-3B-Instruct model parameters.
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```
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ollama show llama3.2 --modelfile > Modelfile
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```
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4. Modify Modelfile, Remove all comment lines (indicated by #) before the "FROM" keyword. Replace the "FROM" with the following content.
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```
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FROM huihui-ai/Llama-3.2-3B-Instruct-abliterated
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```
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5. Use ollama create to then create the quantized model.
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```
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ollama create --quantize q4_K_M -f Modelfile Llama-3.2-3B-Instruct-abliterated-q4_K_M
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```
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6. Run model
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```
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ollama run Llama-3.2-3B-Instruct-abliterated-q4_K_M
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```
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The running architecture is llama.
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## Evaluations
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The following data has been re-evaluated and calculated as the average for each test.
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| Benchmark | Llama-3.2-3B-Instruct | Llama-3.2-3B-Instruct-abliterated |
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|-------------|-----------------------|-----------------------------------|
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| IF_Eval | 76.55 | **76.76** |
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| MMLU Pro | 27.88 | **28.00** |
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| TruthfulQA | 50.55 | **50.73** |
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| BBH | 41.81 | **41.86** |
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| GPQA | 28.39 | **28.41** |
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The script used for evaluation can be found inside this repository under /eval.sh, or click [here](https://huggingface.co/huihui-ai/Llama-3.2-3B-Instruct-abliterated/blob/main/eval.sh)
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