initial: sygnif-lora-v2 (Qwen 3.5 9B QLoRA r=16, FC, 89.5% acc)

.gitattributes

@@ -33,3 +33,5 @@ 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
+sygnif-lora-v2.gguf filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,145 @@
+---
+license: apache-2.0
+base_model: Qwen/Qwen3.5-9B
+library_name: peft
+tags:
+  - lora
+  - peft
+  - qwen3.5
+  - function-calling
+  - tool-use
+  - sygnif
+  - hermes-format
+datasets:
+  - lockon/xlam-function-calling-60k
+  - NousResearch/hermes-function-calling-v1
+language:
+  - en
+---
+
+# sygnif-lora-v2
+
+LoRA adapter trained on **`Qwen/Qwen3.5-9B`** for tool-calling in
+[Hermes `<tool_call>{...}</tool_call>`](https://huggingface.co/NousResearch/hermes-function-calling-v1)
+format, with a small voice-replay slice from a SYGNIF crypto trading agent's
+channeler corpus.
+
+The adapter teaches structured function-calling grammar; **specific tool
+names are provided at inference time via the system prompt's `<tools>[…]</tools>`
+block**, not learned. This is the standard Hermes-style FC convention.
+
+## Training summary
+
+| Field | Value |
+|---|---|
+| Base model | `Qwen/Qwen3.5-9B` (Apache 2.0, ungated) |
+| Method | QLoRA (4-bit NF4 base, double-quant) + LoRA r=16 |
+| Trainable params | 29,097,984 / 8,982,901,248 = **0.32 %** |
+| Target modules | `q_proj`, `k_proj`, `v_proj`, `o_proj`, `gate_proj`, `up_proj`, `down_proj` |
+| Effective batch | 16 (per-device 1 × grad-accum 16) |
+| Max seq | 1536 tokens |
+| Learning rate | 2e-4, cosine schedule |
+| Epochs | 2 |
+| Steps | 498 |
+| Hardware | 1× RTX 4090 24 GB |
+| Wall time | 5 h 40 min |
+
+## Final metrics
+
+| Metric | Start (step 10) | End (step 490) | Best |
+|---|---|---|---|
+| Train loss | 1.0879 | **0.3600** | 0.3276 (step 360) |
+| Mean token accuracy | 75.85 % | **89.51 %** | 90.01 % (step 360) |
+
+Slight uptick at the very end (loss 0.33 → 0.36 over the last 80 steps) is
+LR-schedule-tail noise; the model is at convergence by step ~360.
+
+## Training corpus (3,969 rows, ChatML)
+
+| Slice | Rows | Source |
+|---|---|---|
+| Single-turn FC | ~2,000 | [`lockon/xlam-function-calling-60k`](https://huggingface.co/datasets/lockon/xlam-function-calling-60k) (CC-BY-4.0 mirror of gated `Salesforce/xlam-function-calling-60k`) |
+| Multi-turn FC + tool role | ~1,500 | [`NousResearch/hermes-function-calling-v1`](https://huggingface.co/datasets/NousResearch/hermes-function-calling-v1) (Apache 2.0) |
+| Voice replay | 472 | SYGNIF channeler corpus (private — your data) |
+
+All rows normalized to ChatML `messages` format with `<tool_call>{...}</tool_call>`
+in assistant turns and `<tool_response>{...}</tool_response>` in tool turns.
+
+## Files
+
+| File | Purpose |
+|---|---|
+| `adapter_model.safetensors` | PEFT LoRA weights, 56 MB |
+| `adapter_config.json` | PEFT config (r, alpha, target_modules, etc.) |
+| `adapter_metadata.json` | Reproducibility sidecar — full hyperparams + train timestamp |
+| `chat_template.jinja` | Qwen 3.5 chat template (incl. tool role) |
+| `tokenizer.json` + `tokenizer_config.json` | Tokenizer files |
+| `sygnif-lora-v2.gguf` | Same adapter in llama.cpp GGUF format, 56 MB — for `llama-server --lora` |
+
+## Usage
+
+### transformers + peft
+
+```python
+from peft import PeftModel
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+base = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3.5-9B", torch_dtype="bfloat16")
+tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3.5-9B")
+model = PeftModel.from_pretrained(base, "gianson/sygnif-lora-v2")
+
+messages = [
+    {"role": "system", "content": "You are a tool-using assistant. Use tools when asked for live data.\n\n<tools>\n[...your tool schemas...]\n</tools>"},
+    {"role": "user",   "content": "What's BTC's current price?"},
+]
+inputs = tokenizer.apply_chat_template(messages, return_tensors="pt", add_generation_prompt=True)
+out = model.generate(inputs, max_new_tokens=300)
+print(tokenizer.decode(out[0][inputs.shape[1]:], skip_special_tokens=False))
+# → <tool_call>{"name":"btc_ticker","arguments":{"symbol":"BTCUSDT"}}</tool_call>
+```
+
+### llama.cpp / llama-server
+
+```bash
+llama-server \
+  --model /path/to/Qwen3.5-9B-Q4_K_M.gguf \
+  --lora  /path/to/sygnif-lora-v2.gguf \
+  --jinja --ctx-size 4096 --port 8080 --n-gpu-layers 99
+```
+
+Then hit `/v1/chat/completions` (OpenAI-compatible) — the model emits
+`tool_calls=[{...}]` per the Hermes convention.
+
+## Verified behavior
+
+- **Emits structured `tool_calls` arrays**, not free-form text or hallucinated tool names.
+- **Skips tool-calling on conversational queries** ("evaluate your skills") — uses the negatives in xlam to hold the line.
+- **Reasoning trace via Qwen 3.5 thinking-mode** in `reasoning_content` field.
+- Final response throughput ~113 tok/s on RTX 4090, ~3 tok/s on Intel CPU (Q4 base).
+
+## Known limitations
+
+- **No prior on specific tool names.** The training corpus uses generic FC tool names; for your specific tools (e.g. `btc.ticker`, `chain.balance`), provide them in the system prompt's `<tools>[…]</tools>` block. The model dispatches what's there.
+- Trained at 4-bit base (NF4 + double-quant) — bf16 retraining at r=32 would likely add ~1–2 pp accuracy. Skipped here because no 48 GB GPU was in stock at training time.
+
+## License
+
+Apache 2.0 — same as the base model. Trained on:
+- xlam-function-calling-60k: CC-BY-4.0 (attribution to Salesforce/lockon)
+- hermes-function-calling-v1: Apache 2.0 (NousResearch)
+- channeler replay slice: original data (the model author)
+
+No restrictions on commercial use, redistribution, or further fine-tuning.
+
+## Citation
+
+If you use this adapter:
+
+```
+@misc{sygnif-lora-v2,
+  author = {Gianson},
+  title = {sygnif-lora-v2: Hermes-format function-calling LoRA on Qwen 3.5 9B},
+  year  = {2026},
+  url   = {https://huggingface.co/gianson/sygnif-lora-v2}
+}
+```

adapter_config.json

@@ -0,0 +1,48 @@
+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": null,
+  "base_model_name_or_path": "Qwen/Qwen3.5-9B",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 32,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "lora_ga_config": null,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.19.1",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "v_proj",
+    "up_proj",
+    "k_proj",
+    "q_proj",
+    "o_proj",
+    "down_proj",
+    "gate_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_bdlora": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

adapter_metadata.json

@@ -0,0 +1,17 @@
+{
+  "base_model": "Qwen/Qwen3.5-9B",
+  "corpus": "/workspace/sygnif-agent/data/sygnif_tools_sft.jsonl",
+  "n_rows": 3969,
+  "epochs": 2,
+  "batch_size": 1,
+  "grad_accum": 16,
+  "lr": 0.0002,
+  "max_seq": 1536,
+  "lora_r": 16,
+  "lora_alpha": 32,
+  "lora_dropout": 0.05,
+  "seed": 7,
+  "bf16": true,
+  "load_in_4bit": true,
+  "trained_at": "2026-04-27T18:46:12+0000"
+}

adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:1fb93b8c76dea7440ac54cc0bfa51dfabab5132f3a135cb906b44bd1bfb9b5e6
+size 58230048

chat_template.jinja

@@ -0,0 +1,154 @@
+{%- 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 %}
+        {%- if loop.index0 > ns.last_query_index %}
+            {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content + '\n</think>\n\n' + content }}
+        {%- else %}
+            {{- '<|im_start|>' + message.role + '\n' + content }}
+        {%- endif %}
+        {%- 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 %}

sygnif-lora-v2.gguf

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:5df1152c6eeaef692d45597b84514325f2343b048797f3d69f5707826051de6b
+size 58214272

tokenizer.json

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:06b9509352d2af50381ab2247e083b80d32d5c0aba91c272ca9ff729b6a0e523
+size 19989325

tokenizer_config.json

@@ -0,0 +1,32 @@
+{
+  "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": false,
+  "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|>"
+}