Add MNN Q4 conversion for TokForge mobile inference

.gitattributes

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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+llm.mnn filter=lfs diff=lfs merge=lfs -text
+llm.mnn.weight filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,107 @@
+---
+license: apache-2.0
+language:
+  - en
+pipeline_tag: text-generation
+base_model: Goekdeniz-Guelmez/Josiefied-Qwen3-4B-abliterated-v2
+tags:
+  - mnn
+  - qwen3
+  - mobile
+  - on-device
+  - tokforge
+  - uncensored
+  - abliterated
+---
+
+# Josiefied-Qwen3-4B-abliterated-v2-MNN
+
+Pre-converted [Josiefied-Qwen3-4B-abliterated-v2](https://huggingface.co/Goekdeniz-Guelmez/Josiefied-Qwen3-4B-abliterated-v2) in MNN format for on-device inference with [TokForge](https://tokforge.ai).
+
+> **Original model by [Goekdeniz-Guelmez](https://huggingface.co/Goekdeniz-Guelmez)** — converted to MNN Q4 for mobile deployment.
+
+## Model Details
+
+| | |
+|---|---|
+| **Architecture** | Qwen3 (standard multi-head attention, 36 layers) |
+| **Parameters** | 4B (4-bit quantized) |
+| **Format** | MNN (Alibaba Mobile Neural Network) |
+| **Quantization** | W4A16 (4-bit weights, block size 128) |
+| **Vocab** | 151,936 tokens |
+| **Source** | [Goekdeniz-Guelmez/Josiefied-Qwen3-4B-abliterated-v2](https://huggingface.co/Goekdeniz-Guelmez/Josiefied-Qwen3-4B-abliterated-v2) |
+
+## Description
+
+Josiefied abliterated v2 by Goekdeniz Guelmez — refined 4B Qwen3 with abliterated safety filters. The v2 iteration improves on the original with better uncensoring and instruction following. Great balance of speed and quality for everyday mobile use.
+
+## Files
+
+| File | Description |
+|------|-------------|
+| `llm.mnn` | Model computation graph |
+| `llm.mnn.weight` | Quantized weight data (Q4, block=128) |
+| `llm_config.json` | Model config with Jinja chat template |
+| `tokenizer.txt` | Tokenizer vocabulary |
+| `config.json` | MNN runtime config |
+
+## Usage with TokForge
+
+This model is optimized for **[TokForge](https://tokforge.ai)** — a free Android app for private, on-device LLM inference.
+
+1. Download [TokForge from the Play Store](https://tokforge.ai)
+2. Open the app → Models → Download this model
+3. Start chatting — runs 100% locally, no internet required
+
+### Recommended Settings
+
+| Setting | Value |
+|---------|-------|
+| Backend | OpenCL (Qualcomm) / Vulkan (MediaTek) / CPU (fallback) |
+| Precision | Low |
+| Threads | 4 |
+| Thinking | Off (or On for thinking-capable models) |
+
+### Speculative Decoding
+
+Pair with the [TokForge Acceleration Pack](https://huggingface.co/darkmaniac7/TokForge-AccelerationPack-Draft) for **+20-38% faster generation** on supported devices.
+
+| Device | SoC | AR | With Draft | Uplift |
+|---|---|---|---|---|
+| Lenovo TB520FU | SM8650 | 17.7 tok/s | 24.4 tok/s | **+38%** |
+| RedMagic 11 Pro | SM8850 | 24.0 tok/s | ~28 tok/s | **+17%** |
+
+## Performance
+
+Actual speed varies by device, thermal state, and generation length. Typical ranges for this model size:
+
+| Device Class | SoC Example | Backend | Approx. tok/s |
+|---|---|---|---|
+| Flagship 2025 | SM8850 | OpenCL | ~17-24 tok/s |
+| Mid-range 2024 | SM8650 | OpenCL | ~14-18 tok/s |
+| Budget 2024 | SM8635 | CPU | ~9-12 tok/s |
+| MediaTek D9400 | MT6991 | Vulkan | ~14 tok/s |
+
+## Attribution
+
+This is an MNN conversion of **[Josiefied-Qwen3-4B-abliterated-v2](https://huggingface.co/Goekdeniz-Guelmez/Josiefied-Qwen3-4B-abliterated-v2)** by **[Goekdeniz-Guelmez](https://huggingface.co/Goekdeniz-Guelmez)**. All credit for the model architecture, training, and fine-tuning goes to the original author(s). This conversion only changes the runtime format for mobile deployment.
+
+## Limitations
+
+- Intended for TokForge / MNN on-device inference on Android
+- This is a runtime bundle, not a standard Transformers training checkpoint
+- Quantization (Q4) may slightly reduce quality compared to the full-precision original
+- Abliterated/uncensored models have had safety filters removed — **use responsibly**
+
+## Community
+
+- **Website:** [tokforge.ai](https://tokforge.ai)
+- **Discord:** [Join our Discord](https://discord.gg/Acv3CBtfVm)
+- **GitHub:** [TokForge on GitHub](https://github.com/darkmaniac7/Elysium)
+
+## Export Details
+
+Converted using MNN's `llmexport` pipeline:
+```bash
+python llmexport.py --path Goekdeniz-Guelmez/Josiefied-Qwen3-4B-abliterated-v2 --export mnn --quant_bit 4 --quant_block 128
+```

config.json

@@ -0,0 +1,10 @@
+{
+    "llm_model": "llm.mnn",
+    "llm_weight": "llm.mnn.weight",
+    "backend_type": "cpu",
+    "thread_num": 4,
+    "precision": "low",
+    "memory": "low",
+    "sampler_type": "penalty",
+    "penalty": 1.1
+}

export_args.json

@@ -0,0 +1,42 @@
+{
+    "path": "/root/models/hf_convert_queue/Josiefied-Qwen3-4B-abliterated-v2",
+    "type": null,
+    "tokenizer_path": "/root/models/hf_convert_queue/Josiefied-Qwen3-4B-abliterated-v2",
+    "eagle_path": null,
+    "lora_path": null,
+    "gptq_path": null,
+    "dst_path": "/root/models/hf_uploads/Josiefied-Qwen3-4B-abliterated-v2-MNN",
+    "verbose": false,
+    "test": null,
+    "export": "mnn",
+    "onnx_slim": false,
+    "quant_bit": 4,
+    "quant_block": 128,
+    "visual_quant_bit": null,
+    "visual_quant_block": null,
+    "lm_quant_bit": 4,
+    "lm_quant_block": 128,
+    "mnnconvert": "../../../build/MNNConvert",
+    "ppl": false,
+    "awq": false,
+    "hqq": false,
+    "omni": false,
+    "transformer_fuse": false,
+    "group_conv_native": false,
+    "smooth": false,
+    "sym": false,
+    "visual_sym": false,
+    "seperate_embed": false,
+    "lora_split": false,
+    "calib_data": null,
+    "act_bit": 16,
+    "embed_bit": 16,
+    "act_sym": false,
+    "quant_config": null,
+    "generate_for_npu": false,
+    "skip_weight": false,
+    "omni_epochs": 20,
+    "omni_lr": 0.005,
+    "omni_wd": 0.0001,
+    "tie_word_embeddings": true
+}

llm.mnn

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+oid sha256:91abf52c44be37545762d78439afb0c26f5deb031567c262b7126d3410b9102f
+size 645760

llm.mnn.weight

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+version https://git-lfs.github.com/spec/v1
+oid sha256:2f5b620b46e043ad6700ae55e063bbf933fe4c6fd378f5dd7211195abdbfb37c
+size 2264102338

llm_config.json

@@ -0,0 +1,18 @@
+{
+    "model_type": "qwen3",
+    "hidden_size": 2560,
+    "attention_mask": "float",
+    "attention_type": "full",
+    "is_mrope": false,
+    "jinja": {
+        "chat_template": "{%- if tools %}\n    {{- '<|im_start|>system\\n' }}\n    {%- if messages[0].role == 'system' %}\n        {{- messages[0].content + '\\n\\n' }}\n    {%- endif %}\n    {{- \"# Tools\\n\\nYou may call one or more functions to assist with the user query.\\n\\nYou are provided with function signatures within <tools></tools> XML tags:\\n<tools>\" }}\n    {%- for tool in tools %}\n        {{- \"\\n\" }}\n        {{- tool | tojson }}\n    {%- endfor %}\n    {{- \"\\n</tools>\\n\\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\\n<tool_call>\\n{\\\"name\\\": <function-name>, \\\"arguments\\\": <args-json-object>}\\n</tool_call><|im_end|>\\n\" }}\n{%- else %}\n    {%- if messages[0].role == 'system' %}\n        {{- '<|im_start|>system\\n' + messages[0].content + '<|im_end|>\\n' }}\n    {%- endif %}\n{%- endif %}\n{%- set ns = namespace(multi_step_tool=true, last_query_index=messages|length - 1) %}\n{%- for message in messages[::-1] %}\n    {%- set index = (messages|length - 1) - loop.index0 %}\n    {%- if ns.multi_step_tool and message.role == \"user\" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}\n        {%- set ns.multi_step_tool = false %}\n        {%- set ns.last_query_index = index %}\n    {%- endif %}\n{%- endfor %}\n{%- for message in messages %}\n    {%- if message.content is string %}\n        {%- set content = message.content %}\n    {%- else %}\n        {%- set content = '' %}\n    {%- endif %}\n    {%- if (message.role == \"user\") or (message.role == \"system\" and not loop.first) %}\n        {{- '<|im_start|>' + message.role + '\\n' + content + '<|im_end|>' + '\\n' }}\n    {%- elif message.role == \"assistant\" %}\n        {%- set reasoning_content = '' %}\n        {%- if message.reasoning_content is string %}\n            {%- set reasoning_content = message.reasoning_content %}\n        {%- else %}\n            {%- if '</think>' in content %}\n                {%- set reasoning_content = content.split('</think>')[0].rstrip('\\n').split('<think>')[-1].lstrip('\\n') %}\n                {%- set content = content.split('</think>')[-1].lstrip('\\n') %}\n            {%- endif %}\n        {%- endif %}\n        {%- if loop.index0 > ns.last_query_index %}\n            {%- if loop.last or (not loop.last and reasoning_content) %}\n                {{- '<|im_start|>' + message.role + '\\n<think>\\n' + reasoning_content.strip('\\n') + '\\n</think>\\n\\n' + content.lstrip('\\n') }}\n            {%- else %}\n                {{- '<|im_start|>' + message.role + '\\n' + content }}\n            {%- endif %}\n        {%- else %}\n            {{- '<|im_start|>' + message.role + '\\n' + content }}\n        {%- endif %}\n        {%- if message.tool_calls %}\n            {%- for tool_call in message.tool_calls %}\n                {%- if (loop.first and content) or (not loop.first) %}\n                    {{- '\\n' }}\n                {%- endif %}\n                {%- if tool_call.function %}\n                    {%- set tool_call = tool_call.function %}\n                {%- endif %}\n                {{- '<tool_call>\\n{\"name\": \"' }}\n                {{- tool_call.name }}\n                {{- '\", \"arguments\": ' }}\n                {%- if tool_call.arguments is string %}\n                    {{- tool_call.arguments }}\n                {%- else %}\n                    {{- tool_call.arguments | tojson }}\n                {%- endif %}\n                {{- '}\\n</tool_call>' }}\n            {%- endfor %}\n        {%- endif %}\n        {{- '<|im_end|>\\n' }}\n    {%- elif message.role == \"tool\" %}\n        {%- if loop.first or (messages[loop.index0 - 1].role != \"tool\") %}\n            {{- '<|im_start|>user' }}\n        {%- endif %}\n        {{- '\\n<tool_response>\\n' }}\n        {{- content }}\n        {{- '\\n</tool_response>' }}\n        {%- if loop.last or (messages[loop.index0 + 1].role != \"tool\") %}\n            {{- '<|im_end|>\\n' }}\n        {%- endif %}\n    {%- endif %}\n{%- endfor %}\n{%- if add_generation_prompt %}\n    {{- '<|im_start|>assistant\\n' }}\n{%- endif %}",
+        "eos": "<|im_end|>"
+    },
+    "tie_embeddings": [
+        2045314498,
+        2239792578,
+        24309760,
+        4,
+        128
+    ]
+}