Ornith 1.5 9B uncensored — full-precision abliterated weights (vision preserved)

.gitattributes

@@ -33,3 +33,6 @@ 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
+assets/ornith_9b_eval.png filter=lfs diff=lfs merge=lfs -text
+assets/ornith_logo.png filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,113 @@
+---
+license: apache-2.0
+base_model: ornith-ai/Ornith-1.5-9B
+library_name: transformers
+pipeline_tag: image-text-to-text
+tags:
+- ornith
+- qwen3_5
+- abliterated
+- uncensored
+- zerofuse
+- multimodal
+- vision
+---
+
+# Ornith-1.5-9B-uncensored
+
+An **abliterated** (refusal-direction-ablated) build of
+[`ornith-ai/Ornith-1.5-9B`](https://huggingface.co/ornith-ai/Ornith-1.5-9B), produced with
+[ZeroFuse](https://github.com/junainfinity/ZeroFuse) and published by
+[junafinity](https://huggingface.co/junafinity).
+
+**Vision tower and MTP heads are preserved** — see
+[Vision & MTP preservation](#vision--mtp-preservation) for the before/after audit.
+
+## Variants in this family
+
+| Model | Base | Format | Precision | Notes |
+|---|---|---|---|---|
+| **Ornith-1.5-9B-uncensored** ← *you are here* | Ornith-1.5-9B | Safetensors (bf16) | 16-bit | Full-precision abliterated weights |
+| [Ornith-1.5-9B-uncensored-MLX-8bit](https://huggingface.co/junafinity/Ornith-1.5-9B-uncensored-MLX-8bit) | Ornith-1.5-9B | MLX | 8-bit | Apple-silicon MLX build |
+| [Ornith-1.5-9B-uncensored-GGUF-8bit](https://huggingface.co/junafinity/Ornith-1.5-9B-uncensored-GGUF-8bit) | Ornith-1.5-9B | GGUF | Q8_0 | llama.cpp build |
+| [Ornith-1.5-35B-A3B-uncensored-MLX-8bit](https://huggingface.co/junafinity/Ornith-1.5-35B-A3B-uncensored-MLX-8bit) | Ornith-1.5-35B-A3B | MLX | 8-bit | Apple-silicon MLX build |
+| [Ornith-1.5-35B-A3B-uncensored-GGUF-8bit](https://huggingface.co/junafinity/Ornith-1.5-35B-A3B-uncensored-GGUF-8bit) | Ornith-1.5-35B-A3B | GGUF | Q8_0 | llama.cpp build |
+
+## Vision & MTP preservation
+
+**Both the vision tower and any multi-token-prediction (MTP) block are preserved.**
+Abliteration is applied *only* to the residual-writing projections inside the
+language-model decoder stack — `self_attn.o_proj`, `linear_attn.out_proj` and
+`mlp.down_proj` (including MoE experts). The vision tower and `mtp.*` tensors are
+never read and never written by the weight edit, so they carry through unchanged
+by construction.
+
+Audited at the **start and end** of the abliteration run:
+
+| Component | Before | After | Status |
+|---|---|---|---|
+| **Vision tower** | 333 tensors / 456,010,480 params | 333 tensors / 456,010,480 params | ✅ **preserved** — bit-identical |
+| **MTP head** | not present in base | not present | ➖ none in this lineage |
+
+**Verification performed:**
+
+- Tensor-name and parameter-count audit of the checkpoint before and after the run.
+- SHA-256 comparison of raw tensor bytes: sampled vision-tower weights are **bit-identical** pre/post, as are all non-target language-model weights; only the intended abliteration targets differ.
+- End-to-end multimodal generation on the abliterated weights (image in → description out), confirming the vision path is not merely present but functional.
+
+> **On MTP, precisely:** the base checkpoint's `config.json` declares `mtp_num_hidden_layers: 1`, but the published weights ship **no** `mtp.*` tensors — there is no MTP block in this lineage to begin with. Nothing was removed and nothing was lost; the pipeline preserves `mtp.*` tensors wherever a checkpoint actually provides them.
+
+## Abliteration result
+
+| Metric | Value |
+|---|---|
+| Refusals on held-out harmful set | **9 → 0** / 64 |
+| KL divergence from base | **0.001668** |
+| Optuna trials | 100 |
+| Pareto points | 4 |
+| Selected trial | #90 |
+| Ablation strength | 1.343 |
+| Layers edited | 15–20 of 32 |
+| Direction source layer | 20 |
+
+ZeroFuse co-minimizes two objectives — remaining refusals and KL divergence from the
+original model — with a multi-objective Optuna TPE search, then materializes the
+selected point on the Pareto front as a direct weight edit
+(`W' = W − strength · r(rᵀW)`). There is no runtime adapter and no inference-time
+overhead: the result is a standard checkpoint of identical shape and speed.
+
+The very low KL (0.001668) means the output distribution on harmless
+prompts is nearly unchanged from the base model, i.e. refusal behaviour was removed
+with minimal collateral effect on general capability.
+
+## Method
+
+1. Residual-stream activations captured on harmful vs. harmless prompt sets.
+2. Refusal direction estimated by difference-of-means, with projected refinement.
+3. Two-objective Optuna TPE search over source layer, layer span and strength.
+4. The selected configuration orthogonalized out of the residual-writing weights.
+
+## Usage
+
+```python
+from transformers import AutoModelForImageTextToText, AutoProcessor
+
+model = AutoModelForImageTextToText.from_pretrained(
+    "junafinity/Ornith-1.5-9B-uncensored", dtype="auto", device_map="auto"
+)
+processor = AutoProcessor.from_pretrained("junafinity/Ornith-1.5-9B-uncensored")
+```
+
+> Requires `transformers >= 5.12` for the `qwen3_5` architecture.
+
+## Responsible use
+
+This model has had safety guardrails **reduced or removed**. You are responsible for
+compliance with the base model's license and acceptable-use policy, applicable law,
+and the terms of any platform you deploy on. Removing guardrails does not remove
+accountability.
+
+---
+
+*Abliterated with [ZeroFuse](https://github.com/junainfinity/ZeroFuse) · base model
+[ornith-ai/Ornith-1.5-9B](https://huggingface.co/ornith-ai/Ornith-1.5-9B)*

chat_template.jinja

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+{%- set image_count = namespace(value=0) %}
+{%- set video_count = namespace(value=0) %}
+{%- macro render_content(content, do_vision_count, is_system_content=false) %}
+    {%- if content is string %}
+        {{- content }}
+    {%- elif content is iterable and content is not mapping %}
+        {%- for item in content %}
+            {%- if 'image' in item or 'image_url' in item or item.type == 'image' %}
+                {%- if is_system_content %}
+                    {{- raise_exception('System message cannot contain images.') }}
+                {%- endif %}
+                {%- if do_vision_count %}
+                    {%- set image_count.value = image_count.value + 1 %}
+                {%- endif %}
+                {%- if add_vision_id %}
+                    {{- 'Picture ' ~ image_count.value ~ ': ' }}
+                {%- endif %}
+                {{- '<|vision_start|><|image_pad|><|vision_end|>' }}
+            {%- elif 'video' in item or item.type == 'video' %}
+                {%- if is_system_content %}
+                    {{- raise_exception('System message cannot contain videos.') }}
+                {%- endif %}
+                {%- if do_vision_count %}
+                    {%- set video_count.value = video_count.value + 1 %}
+                {%- endif %}
+                {%- if add_vision_id %}
+                    {{- 'Video ' ~ video_count.value ~ ': ' }}
+                {%- endif %}
+                {{- '<|vision_start|><|video_pad|><|vision_end|>' }}
+            {%- elif 'text' in item %}
+                {{- item.text }}
+            {%- else %}
+                {{- raise_exception('Unexpected item type in content.') }}
+            {%- endif %}
+        {%- endfor %}
+    {%- elif content is none or content is undefined %}
+        {{- '' }}
+    {%- else %}
+        {{- raise_exception('Unexpected content type.') }}
+    {%- endif %}
+{%- endmacro %}
+{%- if not messages %}
+    {{- raise_exception('No messages provided.') }}
+{%- endif %}
+{%- if tools and tools is iterable and tools is not mapping %}
+    {{- '<|im_start|>system\n' }}
+    {{- "# Tools\n\nYou have access to the following functions:\n\n<tools>" }}
+    {%- for tool in tools %}
+        {{- "\n" }}
+        {{- tool | tojson }}
+    {%- endfor %}
+    {{- "\n</tools>" }}
+    {{- '\n\nIf you choose to call a function ONLY reply in the following format with NO suffix:\n\n<tool_call>\n<function=example_function_name>\n<parameter=example_parameter_1>\nvalue_1\n</parameter>\n<parameter=example_parameter_2>\nThis is the value for the second parameter\nthat can span\nmultiple lines\n</parameter>\n</function>\n</tool_call>\n\n<IMPORTANT>\nReminder:\n- Function calls MUST follow the specified format: an inner <function=...></function> block must be nested within <tool_call></tool_call> XML tags\n- Required parameters MUST be specified\n- You may provide optional reasoning for your function call in natural language BEFORE the function call, but NOT after\n- If there is no function call available, answer the question like normal with your current knowledge and do not tell the user about function calls\n</IMPORTANT>' }}
+    {%- if messages[0].role == 'system' %}
+        {%- set content = render_content(messages[0].content, false, true)|trim %}
+        {%- if content %}
+            {{- '\n\n' + content }}
+        {%- endif %}
+    {%- endif %}
+    {{- '<|im_end|>\n' }}
+{%- else %}
+    {%- if messages[0].role == 'system' %}
+        {%- set content = render_content(messages[0].content, false, true)|trim %}
+        {{- '<|im_start|>system\n' + content + '<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}
+{%- for message in messages[::-1] %}
+    {%- set index = (messages|length - 1) - loop.index0 %}
+    {%- if ns.multi_step_tool and message.role == "user" %}
+        {%- set content = render_content(message.content, false)|trim %}
+        {%- if not(content.startswith('<tool_response>') and content.endswith('</tool_response>')) %}
+            {%- set ns.multi_step_tool = false %}
+            {%- set ns.last_query_index = index %}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if ns.multi_step_tool %}
+    {{- raise_exception('No user query found in messages.') }}
+{%- endif %}
+{%- for message in messages %}
+    {%- set content = render_content(message.content, true)|trim %}
+    {%- if message.role == "system" %}
+        {%- if not loop.first %}
+            {{- raise_exception('System message must be at the beginning.') }}
+        {%- endif %}
+    {%- elif message.role == "user" %}
+        {{- '<|im_start|>' + message.role + '\n' + content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {%- set reasoning_content = '' %}
+        {%- if message.reasoning_content is string %}
+            {%- set reasoning_content = message.reasoning_content %}
+        {%- else %}
+            {%- if '</think>' in content %}
+                {%- set reasoning_content = content.split('</think>')[0].rstrip('\n').split('<think>')[-1].lstrip('\n') %}
+                {%- set content = content.split('</think>')[-1].lstrip('\n') %}
+            {%- endif %}
+        {%- endif %}
+        {%- set reasoning_content = reasoning_content|trim %}
+        {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
+        {%- if message.tool_calls and message.tool_calls is iterable and message.tool_calls is not mapping %}
+            {%- for tool_call in message.tool_calls %}
+                {%- if tool_call.function is defined %}
+                    {%- set tool_call = tool_call.function %}
+                {%- endif %}
+                {%- if loop.first %}
+                    {%- if content|trim %}
+                        {{- '\n\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
+                    {%- else %}
+                        {{- '<tool_call>\n<function=' + tool_call.name + '>\n' }}
+                    {%- endif %}
+                {%- else %}
+                    {{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
+                {%- endif %}
+                {%- if tool_call.arguments is defined %}
+                    {%- for args_name, args_value in tool_call.arguments|items %}
+                        {{- '<parameter=' + args_name + '>\n' }}
+                        {%- set args_value = args_value | tojson | safe if args_value is mapping or (args_value is sequence and args_value is not string) else args_value | string %}
+                        {{- args_value }}
+                        {{- '\n</parameter>\n' }}
+                    {%- endfor %}
+                {%- endif %}
+                {{- '</function>\n</tool_call>' }}
+            {%- endfor %}
+        {%- endif %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if loop.previtem and loop.previtem.role != "tool" %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- content }}
+        {{- '\n</tool_response>' }}
+        {%- if not loop.last and loop.nextitem.role != "tool" %}
+            {{- '<|im_end|>\n' }}
+        {%- elif loop.last %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- else %}
+        {{- raise_exception('Unexpected message role.') }}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+    {%- if enable_thinking is defined and enable_thinking is false %}
+        {{- '<think>\n\n</think>\n\n' }}
+    {%- else %}
+        {{- '<think>\n' }}
+    {%- endif %}
+{%- endif %}

config.json

@@ -0,0 +1,112 @@
+{
+  "architectures": [
+    "Qwen3_5ForConditionalGeneration"
+  ],
+  "dtype": "bfloat16",
+  "eos_token_id": 248046,
+  "hidden_size": 4096,
+  "image_token_id": 248056,
+  "model_type": "qwen3_5",
+  "pad_token_id": 248044,
+  "text_config": {
+    "attention_bias": false,
+    "attention_dropout": 0.0,
+    "attn_output_gate": true,
+    "bos_token_id": null,
+    "dtype": "bfloat16",
+    "eos_token_id": 248044,
+    "full_attention_interval": 4,
+    "head_dim": 256,
+    "hidden_act": "silu",
+    "hidden_size": 4096,
+    "initializer_range": 0.02,
+    "intermediate_size": 12288,
+    "layer_types": [
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention",
+      "linear_attention",
+      "linear_attention",
+      "linear_attention",
+      "full_attention"
+    ],
+    "linear_conv_kernel_dim": 4,
+    "linear_key_head_dim": 128,
+    "linear_num_key_heads": 16,
+    "linear_num_value_heads": 32,
+    "linear_value_head_dim": 128,
+    "mamba_ssm_dtype": "float32",
+    "max_position_embeddings": 262144,
+    "mlp_only_layers": [],
+    "model_type": "qwen3_5_text",
+    "mtp_num_hidden_layers": 1,
+    "mtp_use_dedicated_embeddings": false,
+    "num_attention_heads": 16,
+    "num_hidden_layers": 32,
+    "num_key_value_heads": 4,
+    "pad_token_id": 248044,
+    "partial_rotary_factor": 0.25,
+    "rms_norm_eps": 1e-06,
+    "rope_parameters": {
+      "mrope_interleaved": true,
+      "mrope_section": [
+        11,
+        11,
+        10
+      ],
+      "partial_rotary_factor": 0.25,
+      "rope_theta": 10000000,
+      "rope_type": "default"
+    },
+    "tie_word_embeddings": false,
+    "use_cache": false,
+    "vocab_size": 248320
+  },
+  "tie_word_embeddings": false,
+  "transformers_version": "5.15.1",
+  "video_token_id": 248057,
+  "vision_config": {
+    "deepstack_visual_indexes": [],
+    "depth": 27,
+    "dtype": "bfloat16",
+    "hidden_act": "gelu_pytorch_tanh",
+    "hidden_size": 1152,
+    "in_channels": 3,
+    "initializer_range": 0.02,
+    "intermediate_size": 4304,
+    "model_type": "qwen3_5_vision",
+    "num_heads": 16,
+    "num_position_embeddings": 2304,
+    "out_hidden_size": 4096,
+    "patch_size": 16,
+    "spatial_merge_size": 2,
+    "temporal_patch_size": 2
+  },
+  "vision_end_token_id": 248054,
+  "vision_start_token_id": 248053
+}

generation_config.json

@@ -0,0 +1,7 @@
+{
+  "_from_model_config": true,
+  "eos_token_id": 248046,
+  "pad_token_id": 248044,
+  "transformers_version": "5.15.1",
+  "use_cache": false
+}

model.safetensors

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+oid sha256:20c59628206bcbbfae378218a17a385c7647e48b786a92a659d68a752f523b7f
+size 18819722392

preprocessor_config.json

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+{
+    "size": {
+        "longest_edge": 16777216,
+        "shortest_edge": 65536
+    },
+    "patch_size": 16,
+    "temporal_patch_size": 2,
+    "merge_size": 2,
+    "image_mean": [
+        0.5,
+        0.5,
+        0.5
+    ],
+    "image_std": [
+        0.5,
+        0.5,
+        0.5
+    ],
+    "processor_class": "Qwen3VLProcessor",
+    "image_processor_type": "Qwen2VLImageProcessorFast"
+}

processor_config.json

@@ -0,0 +1,60 @@
+{
+  "image_processor": {
+    "do_convert_rgb": true,
+    "do_normalize": true,
+    "do_rescale": true,
+    "do_resize": true,
+    "image_mean": [
+      0.5,
+      0.5,
+      0.5
+    ],
+    "image_processor_type": "Qwen2VLImageProcessor",
+    "image_std": [
+      0.5,
+      0.5,
+      0.5
+    ],
+    "merge_size": 2,
+    "patch_size": 16,
+    "resample": 3,
+    "rescale_factor": 0.00392156862745098,
+    "size": {
+      "longest_edge": 16777216,
+      "shortest_edge": 65536
+    },
+    "temporal_patch_size": 2
+  },
+  "processor_class": "Qwen3VLProcessor",
+  "video_processor": {
+    "do_convert_rgb": true,
+    "do_normalize": true,
+    "do_rescale": true,
+    "do_resize": true,
+    "do_sample_frames": true,
+    "fps": 2,
+    "image_mean": [
+      0.5,
+      0.5,
+      0.5
+    ],
+    "image_std": [
+      0.5,
+      0.5,
+      0.5
+    ],
+    "max_frames": 768,
+    "merge_size": 2,
+    "min_frames": 4,
+    "patch_size": 16,
+    "resample": 3,
+    "rescale_factor": 0.00392156862745098,
+    "return_metadata": false,
+    "size": {
+      "longest_edge": 25165824,
+      "shortest_edge": 4096
+    },
+    "temporal_patch_size": 2,
+    "video_processor_type": "Qwen3VLVideoProcessor"
+  }
+}

tokenizer.json

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+size 19989492

tokenizer_config.json

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+{
+  "add_prefix_space": false,
+  "audio_bos_token": "<|audio_start|>",
+  "audio_eos_token": "<|audio_end|>",
+  "audio_token": "<|audio_pad|>",
+  "backend": "tokenizers",
+  "bos_token": null,
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "<|im_end|>",
+  "errors": "replace",
+  "image_token": "<|image_pad|>",
+  "is_local": true,
+  "local_files_only": false,
+  "model_max_length": 262144,
+  "model_specific_special_tokens": {
+    "audio_bos_token": "<|audio_start|>",
+    "audio_eos_token": "<|audio_end|>",
+    "audio_token": "<|audio_pad|>",
+    "image_token": "<|image_pad|>",
+    "video_token": "<|video_pad|>",
+    "vision_bos_token": "<|vision_start|>",
+    "vision_eos_token": "<|vision_end|>"
+  },
+  "pad_token": "<|endoftext|>",
+  "pretokenize_regex": "(?i:'s|'t|'re|'ve|'m|'ll|'d)|[^\\r\\n\\p{L}\\p{N}]?[\\p{L}\\p{M}]+|\\p{N}| ?[^\\s\\p{L}\\p{M}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+",
+  "split_special_tokens": false,
+  "tokenizer_class": "Qwen2Tokenizer",
+  "unk_token": null,
+  "video_token": "<|video_pad|>",
+  "vision_bos_token": "<|vision_start|>",
+  "vision_eos_token": "<|vision_end|>"
+}

video_preprocessor_config.json

@@ -0,0 +1,21 @@
+{
+    "size": {
+        "longest_edge": 25165824,
+        "shortest_edge": 4096
+    },
+    "patch_size": 16,
+    "temporal_patch_size": 2,
+    "merge_size": 2,
+    "image_mean": [
+        0.5,
+        0.5,
+        0.5
+    ],
+    "image_std": [
+        0.5,
+        0.5,
+        0.5
+    ],
+    "processor_class": "Qwen3VLProcessor",
+    "video_processor_type": "Qwen3VLVideoProcessor"
+}

zerofuse_run.json

@@ -0,0 +1,97 @@
+{
+  "tool": "zerofuse",
+  "created": "2026-08-19T18:54:11.819286+00:00",
+  "base_model": "/Users/arjun/Projects/Ornith/models/Ornith-1.5-9B",
+  "base_refusals": 9,
+  "selected_trial": {
+    "index": 90,
+    "refusals": 0,
+    "n_bad": 64,
+    "kl": 0.0016684833681210876,
+    "ablation": {
+      "source_layer": 20,
+      "strength": 1.34303331067162,
+      "layer_start": 15,
+      "layer_end": 20
+    }
+  },
+  "config": {
+    "model": "/Users/arjun/Projects/Ornith/models/Ornith-1.5-9B",
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+  }
+}

zerofuse_summary.json

@@ -0,0 +1,62 @@
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+}