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examples/full_study.yaml

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+# Example: Full ablation — all strategies on GPT-2
+# Run with: obliteratus run examples/full_study.yaml
+
+model:
+  name: gpt2
+  task: causal_lm
+  dtype: float32
+  device: cpu
+
+dataset:
+  name: wikitext
+  subset: wikitext-2-raw-v1
+  split: test
+  text_column: text
+  max_samples: 50
+
+strategies:
+  - name: layer_removal
+    params: {}
+  - name: head_pruning
+    params: {}
+  - name: ffn_ablation
+    params: {}
+  - name: embedding_ablation
+    params:
+      chunk_size: 48  # ablate 48 dims at a time (GPT-2 has 768)
+
+metrics:
+  - perplexity
+
+batch_size: 4
+max_length: 256
+output_dir: results/gpt2_full

examples/gpt2_head_ablation.yaml

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+# Example: Ablate every attention head in GPT-2
+# Run with: obliteratus run examples/gpt2_head_ablation.yaml
+
+model:
+  name: gpt2
+  task: causal_lm
+  dtype: float32
+  device: cpu
+
+dataset:
+  name: wikitext
+  subset: wikitext-2-raw-v1
+  split: test
+  text_column: text
+  max_samples: 50
+
+strategies:
+  - name: head_pruning
+    params: {}
+
+metrics:
+  - perplexity
+
+batch_size: 4
+max_length: 256
+output_dir: results/gpt2_heads

examples/gpt2_layer_ablation.yaml

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+# Example: Ablate every layer and FFN block in GPT-2
+# Run with: obliteratus run examples/gpt2_layer_ablation.yaml
+
+model:
+  name: gpt2
+  task: causal_lm
+  dtype: float32
+  device: cpu  # change to "cuda" or "auto" for GPU
+
+dataset:
+  name: wikitext
+  subset: wikitext-2-raw-v1
+  split: test
+  text_column: text
+  max_samples: 100  # keep small for a quick demo
+
+strategies:
+  - name: layer_removal
+    params: {}
+  - name: ffn_ablation
+    params: {}
+
+metrics:
+  - perplexity
+
+batch_size: 4
+max_length: 256
+output_dir: results/gpt2_layers

examples/preset_attention.yaml

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+# Example: Deep-dive into attention heads
+# Uses the "attention" preset — prunes every head individually
+# Run with: obliteratus run examples/preset_attention.yaml
+
+preset: attention
+
+model:
+  name: gpt2
+  task: causal_lm
+  dtype: float32
+  device: cpu
+
+dataset:
+  name: wikitext
+  subset: wikitext-2-raw-v1
+  split: test
+  text_column: text
+
+output_dir: results/gpt2_attention

examples/preset_knowledge.yaml

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+# Example: Find where knowledge is stored (FFNs + embeddings)
+# Run with: obliteratus run examples/preset_knowledge.yaml
+
+preset: knowledge
+
+model:
+  name: gpt2
+  task: causal_lm
+  dtype: float32
+  device: cpu
+
+dataset:
+  name: wikitext
+  subset: wikitext-2-raw-v1
+  split: test
+  text_column: text
+
+output_dir: results/gpt2_knowledge

examples/preset_quick.yaml

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+# Example: Use the "quick" preset for a fast scan
+# This automatically configures layer_removal + ffn_ablation, 25 samples, etc.
+# Run with: obliteratus run examples/preset_quick.yaml
+
+preset: quick
+
+model:
+  name: gpt2
+  task: causal_lm
+  dtype: float32
+  device: cpu
+
+dataset:
+  name: wikitext
+  subset: wikitext-2-raw-v1
+  split: test
+  text_column: text
+
+output_dir: results/gpt2_quick