Upload folder using huggingface_hub

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+qwen3-0.6b-abliterated.q2_k.gguf filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,40 @@
+---
+library_name: transformers
+license: apache-2.0
+license_link: https://huggingface.co/Qwen/Qwen3-0.6B/blob/main/LICENSE
+pipeline_tag: text-generation
+base_model:
+- Qwen/Qwen3-0.6B
+tags:
+- abliteration
+- abliterated
+- autoquant
+- gguf
+---
+
+# 🐹 Qwen3-0.6B-abliterated
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/oCo2RbWkYHjVMsuqXpV5V.png)
+
+<center>Qwen3 Abliterated <a href="https://huggingface.co/mlabonne/Qwen3-0.6B-abliterated">0.6B</a> • <a href="https://huggingface.co/mlabonne/Qwen3-1.7B-abliterated">1.7B</a> • <a href="https://huggingface.co/mlabonne/Qwen3-4B-abliterated">4B</a> • <a href="https://huggingface.co/mlabonne/Qwen3-8B-abliterated">8B</a> • <a href="https://huggingface.co/mlabonne/Qwen3-14B-abliterated">14B</a> • <a href="https://huggingface.co/mlabonne/Qwen3-30B-A3B-abliterated">30B-A3B</a></center>
+
+This is an uncensored version of [Qwen/Qwen3-0.6B](https://huggingface.co/Qwen/Qwen3-0.6B) created with a new abliteration technique.
+See [this article](https://huggingface.co/blog/mlabonne/abliteration) to know more about abliteration.
+
+This is a research project to understand how refusals and latent fine-tuning work in LLMs. 
+I played with different sizes of Qwen3 and noticed there was no one-size-fits-all abliteration strategy. In addition, the reasoning mode interfered with non-reasoning refusals, which made it more challenging. 
+This made me iterate over different recipes and significantly consolidate my scripts with accumulation and better evaluations.
+
+Note that this is fairly experimental, so it might not turn out as well as expected.
+
+I recommend using these generation parameters: `temperature=0.6`, `top_k=20`, `top_p=0.95`, `min_p=0`.
+
+## ✂️ Abliteration
+
+The refusal direction is computed by comparing the residual streams between target (harmful) and baseline (harmless) samples. 
+The hidden states of target modules (e.g., o_proj) are orthogonalized to subtract this refusal direction with a given weight factor. 
+These weight factors follow a normal distribution with a certain spread and peak layer. 
+Modules can be iteratively orthogonalized in batches, or the refusal direction can be accumulated to save memory.
+
+Finally, I used a hybrid evaluation with a dedicated test set to calculate the acceptance rate. This uses both a dictionary approach and [NousResearch/Minos-v1](https://huggingface.co/NousResearch/Minos-v1). 
+The goal is to obtain an acceptance rate >90% and still produce coherent outputs.

qwen3-0.6b-abliterated.q2_k.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:066dcd78cdf0908a1412bd9649e70dfba3f3f87495c7fcd0955bef7b5061ff34
+size 296238208