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README.md

@@ -1,139 +1,209 @@
 ---
-license: apache-2.0
 base_model: Qwen/Qwen3.5-9B
-tags:
-  - qwen3.5
-  - code
-  - tool-calling
-  - lora
-  - sft
-  - unsloth
-  - reasoning
-  - chain-of-thought
-datasets:
-  - nohurry/Opus-4.6-Reasoning-3000x-filtered
-  - Roman1111111/claude-opus-4.6-10000x
-  - TeichAI/claude-4.5-opus-high-reasoning-250x
-  - Jackrong/Qwen3.5-reasoning-700x
-  - togethercomputer/CoderForge-Preview
-language:
-  - en
+library_name: peft
 pipeline_tag: text-generation
+tags:
+- base_model:adapter:Qwen/Qwen3.5-9B
+- dpo
+- lora
+- transformers
+- trl
 ---
 
-# Qwen3.5-DeltaCoder-9B
+# Model Card for Model ID
+
+<!-- Provide a quick summary of what the model is/does. -->
+
+
+
+## Model Details
+
+### Model Description
+
+<!-- Provide a longer summary of what this model is. -->
+
+
+
+- **Developed by:** [More Information Needed]
+- **Funded by [optional]:** [More Information Needed]
+- **Shared by [optional]:** [More Information Needed]
+- **Model type:** [More Information Needed]
+- **Language(s) (NLP):** [More Information Needed]
+- **License:** [More Information Needed]
+- **Finetuned from model [optional]:** [More Information Needed]
+
+### Model Sources [optional]
+
+<!-- Provide the basic links for the model. -->
+
+- **Repository:** [More Information Needed]
+- **Paper [optional]:** [More Information Needed]
+- **Demo [optional]:** [More Information Needed]
+
+## Uses
+
+<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
+
+### Direct Use
 
-A LoRA fine-tune of [Qwen3.5-9B](https://huggingface.co/Qwen/Qwen3.5-9B) trained to improve structured tool-call generation (JSON formatting) for use in coding agents like OpenCode, Pi, and Cline.
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
 
-The fine-tune builds on top of [Jackrong/Qwen3.5-9B-Claude-4.6-Opus-Reasoning-Distilled-v2](https://huggingface.co/Jackrong/Qwen3.5-9B-Claude-4.6-Opus-Reasoning-Distilled-v2), a reasoning distillation of Qwen3.5-9B trained on Claude 4.6 Opus reasoning traces. All datasets used across the full training lineage are listed above.
+[More Information Needed]
 
-## Training Lineage
+### Downstream Use [optional]
 
-```
-Qwen/Qwen3.5-9B-Base
- └─ Qwen/Qwen3.5-9B  (instruction tuned)
-     └─ Jackrong/Qwen3.5-9B-Claude-4.6-Opus-Reasoning-Distilled-v2
-         (SFT on Claude 4.6 Opus reasoning traces for efficient chain-of-thought)
-         Datasets: nohurry/Opus-4.6-Reasoning-3000x-filtered,
-                   Roman1111111/claude-opus-4.6-10000x,
-                   TeichAI/claude-4.5-opus-high-reasoning-250x,
-                   Jackrong/Qwen3.5-reasoning-700x
-         └─ danielcherubini/Qwen3.5-DeltaCoder-9B  ← this model
-             (LoRA SFT on CoderForge-Preview for tool-call reliability)
-             Dataset: togethercomputer/CoderForge-Preview
-```
+<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+
+[More Information Needed]
+
+### Out-of-Scope Use
+
+<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+
+[More Information Needed]
+
+## Bias, Risks, and Limitations
+
+<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+
+[More Information Needed]
+
+### Recommendations
+
+<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+
+Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+
+## How to Get Started with the Model
+
+Use the code below to get started with the model.
+
+[More Information Needed]
 
 ## Training Details
 
-| Parameter | Value |
-|-----------|-------|
-| Base model | Qwen3.5-9B (hybrid GDN architecture) |
-| Method | LoRA (r=64, alpha=32) |
-| Dataset | CoderForge-Preview `filtered_reward1` (50K subset) |
-| Sequence length | 4096 |
-| Batch size | 2 (effective 16 with grad accum 8) |
-| Learning rate | 1e-4 (cosine schedule) |
-| Epochs | 1 |
-| Optimizer | AdamW |
-| Precision | BF16 |
-| Hardware | NVIDIA H200 140GB |
-| Training time | ~10 hours |
-| Framework | Unsloth 2026.3.10 + HuggingFace Transformers 5.3.0 |
+### Training Data
+
+<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+
+[More Information Needed]
+
+### Training Procedure
+
+<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+
+#### Preprocessing [optional]
+
+[More Information Needed]
+
+
+#### Training Hyperparameters
+
+- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+
+#### Speeds, Sizes, Times [optional]
+
+<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+
+[More Information Needed]
+
+## Evaluation
+
+<!-- This section describes the evaluation protocols and provides the results. -->
+
+### Testing Data, Factors & Metrics
+
+#### Testing Data
+
+<!-- This should link to a Dataset Card if possible. -->
+
+[More Information Needed]
+
+#### Factors
+
+<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
+
+[More Information Needed]
+
+#### Metrics
+
+<!-- These are the evaluation metrics being used, ideally with a description of why. -->
+
+[More Information Needed]
+
+### Results
+
+[More Information Needed]
+
+#### Summary
+
+
+
+## Model Examination [optional]
+
+<!-- Relevant interpretability work for the model goes here -->
+
+[More Information Needed]
+
+## Environmental Impact
+
+<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
+
+Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
+
+- **Hardware Type:** [More Information Needed]
+- **Hours used:** [More Information Needed]
+- **Cloud Provider:** [More Information Needed]
+- **Compute Region:** [More Information Needed]
+- **Carbon Emitted:** [More Information Needed]
 
-### LoRA Target Modules
+## Technical Specifications [optional]
 
-All major weight matrices are adapted:
-- **Full Attention** (8/32 layers): `q_proj`, `k_proj`, `v_proj`, `o_proj`
-- **Gated Delta Net** (24/32 layers): `in_proj_qkv`, `in_proj_z`, `in_proj_b`, `in_proj_a`, `out_proj`
-- **MLP** (all 32 layers): `gate_proj`, `up_proj`, `down_proj`
+### Model Architecture and Objective
 
-### Training Loss
+[More Information Needed]
 
-Final training loss: ~0.94 (average: 1.268), decreasing steadily over training.
+### Compute Infrastructure
 
-## Recommended Sampling Settings
+[More Information Needed]
 
-Validated through testing with [ik_llama.cpp](https://github.com/ikawrakow/ik_llama.cpp) and [Kronk](https://github.com/danielcherubini/kronk) on an RTX 3080 10GB.
+#### Hardware
 
-| Profile | temperature | top_k | top_p | min_p | presence_penalty |
-|---------|-------------|-------|-------|-------|-----------------|
-| **Coding** | 0.6 | 20 | 0.95 | 0.0 | 0.0 |
-| **Chat** | 1.0 | 20 | 0.95 | 0.0 | 1.5 |
+[More Information Needed]
 
-> [!WARNING]
-> **Do not use temperature below 0.5** — low temperatures (e.g., 0.3) cause deterministic looping in multi-turn agentic use, where the model repeats the same tool call indefinitely.
+#### Software
 
-### KV Cache Quantization
+[More Information Needed]
 
-For VRAM-constrained GPUs, use quantized KV cache keys/values:
+## Citation [optional]
 
-| Context Length | KV Cache | VRAM (Q4_K_M) | Generation Speed |
-|---------------|----------|---------------|-----------------|
-| 102,400 | f16/q4_0 | ~8.5 GB | ~111 tok/s |
-| 131,072 | f16/q4_0 | ~9.1 GB | ~110 tok/s |
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
 
-```bash
-# llama.cpp / ik_llama.cpp flags
--ctk f16 -ctv q4_0
-```
+**BibTeX:**
 
-## Usage
+[More Information Needed]
 
-### With PEFT
+**APA:**
 
-```python
-from transformers import AutoModelForCausalLM, AutoTokenizer
-from peft import PeftModel
+[More Information Needed]
 
-base_model = AutoModelForCausalLM.from_pretrained(
-    "Jackrong/Qwen3.5-9B-Claude-4.6-Opus-Reasoning-Distilled-v2",
-    trust_remote_code=True,
-)
-model = PeftModel.from_pretrained(base_model, "danielcherubini/Qwen3.5-DeltaCoder-9B")
-tokenizer = AutoTokenizer.from_pretrained("danielcherubini/Qwen3.5-DeltaCoder-9B")
-```
+## Glossary [optional]
 
-### GGUF (Ollama / llama.cpp / LM Studio)
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
 
-Pre-quantized GGUF files available at [danielcherubini/Qwen3.5-DeltaCoder-9B-GGUF](https://huggingface.co/danielcherubini/Qwen3.5-DeltaCoder-9B-GGUF).
+[More Information Needed]
 
-## Benchmarks
+## More Information [optional]
 
-| Model | HumanEval | HumanEval+ |
-|-------|-----------|------------|
-| Jackrong v2 (base) | 53.7% | — |
-| **DeltaCoder-9B** (temp=0.6) | **50.6%** | **49.4%** |
-| DeltaCoder-9B (greedy) | 43.9% | 42.1% |
+[More Information Needed]
 
-Terminal-Bench easy tasks: **2/4 (50%)** — use recommended sampling settings (temp=0.6).
+## Model Card Authors [optional]
 
-## Intended Use
+[More Information Needed]
 
-This model is designed for AI coding agents that rely on structured tool calls (JSON function calling). It improves the base model's ability to generate well-formed tool-call responses in multi-turn agent trajectories.
+## Model Card Contact
 
-## Acknowledgements
+[More Information Needed]
+### Framework versions
 
-- [Unsloth](https://unsloth.ai) for Qwen3.5 training support
-- [Together AI](https://together.ai) for the CoderForge dataset
-- [Jackrong](https://huggingface.co/Jackrong) for the reasoning distillation
-- [Qwen](https://huggingface.co/Qwen) for the base model
+- PEFT 0.18.1

adapter_config.json

@@ -2,12 +2,8 @@
   "alora_invocation_tokens": null,
   "alpha_pattern": {},
   "arrow_config": null,
-  "auto_mapping": {
-    "base_model_class": "Qwen3_5ForConditionalGeneration",
-    "parent_library": "transformers.models.qwen3_5.modeling_qwen3_5",
-    "unsloth_fixed": true
-  },
-  "base_model_name_or_path": "Jackrong/Qwen3.5-9B-Claude-4.6-Opus-Reasoning-Distilled-v2",
+  "auto_mapping": null,
+  "base_model_name_or_path": "Qwen/Qwen3.5-9B",
   "bias": "none",
   "corda_config": null,
   "ensure_weight_tying": false,
@@ -29,22 +25,22 @@
   "peft_type": "LORA",
   "peft_version": "0.18.1",
   "qalora_group_size": 16,
-  "r": 64,
+  "r": 32,
   "rank_pattern": {},
   "revision": null,
   "target_modules": [
+    "in_proj_qkv",
+    "in_proj_z",
+    "q_proj",
+    "k_proj",
     "in_proj_a",
     "up_proj",
-    "k_proj",
-    "in_proj_z",
-    "gate_proj",
-    "down_proj",
     "in_proj_b",
-    "o_proj",
-    "q_proj",
-    "in_proj_qkv",
+    "out_proj",
     "v_proj",
-    "out_proj"
+    "o_proj",
+    "gate_proj",
+    "down_proj"
   ],
   "target_parameters": null,
   "task_type": "CAUSAL_LM",

adapter_model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:87de215f5f35a302a4cad1e4db1f2971a2363b54c1d78b1da645cd1593ac8b9e
-size 692529024
+oid sha256:8ecb70be8d733f91125d4dffdb5747cdca9425915f270e7851a5d8c6f6a2b2fa
+size 346294736

chat_template.jinja

@@ -1,34 +1,90 @@
-{%- if tools %}
-    {{- '<|im_start|>system\n' }}
-    {%- if messages[0].role == 'system' %}
-        {{- messages[0].content + '\n\n' }}
+{%- 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 %}
-    {{- "# 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>" }}
+{%- 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\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</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' %}
-        {{- '<|im_start|>system\n' + messages[0].content + '<|im_end|>\n' }}
+        {%- 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" and message.content is string and not(message.content.startswith('<tool_response>') and message.content.endswith('</tool_response>')) %}
-        {%- set ns.multi_step_tool = false %}
-        {%- set ns.last_query_index = index %}
+    {%- 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 %}
-    {%- if message.content is string %}
-        {%- set content = message.content %}
-    {%- else %}
-        {%- set content = '' %}
-    {%- endif %}
-    {%- if (message.role == "user") or (message.role == "system" and not loop.first) %}
+    {%- 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 = '' %}
@@ -40,49 +96,59 @@
                 {%- set content = content.split('</think>')[-1].lstrip('\n') %}
             {%- endif %}
         {%- endif %}
+        {%- set reasoning_content = reasoning_content|trim %}
         {%- if loop.index0 > ns.last_query_index %}
-            {%- if loop.last or (not loop.last and reasoning_content) %}
-                {{- '<|im_start|>' + message.role + '\n<think>\n' + reasoning_content.strip('\n') + '\n</think>\n\n' + content.lstrip('\n') }}
-            {%- else %}
-                {{- '<|im_start|>' + message.role + '\n' + content }}
-            {%- endif %}
+            {{- '<|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 %}
+        {%- 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 (loop.first and content) or (not loop.first) %}
-                    {{- '\n' }}
-                {%- endif %}
-                {%- if tool_call.function %}
+                {%- if tool_call.function is defined %}
                     {%- set tool_call = tool_call.function %}
                 {%- endif %}
-                {{- '<tool_call>\n{"name": "' }}
-                {{- tool_call.name }}
-                {{- '", "arguments": ' }}
-                {%- if tool_call.arguments is string %}
-                    {{- tool_call.arguments }}
+                {%- 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 %}
-                    {{- tool_call.arguments | tojson }}
+                    {{- '\n<tool_call>\n<function=' + tool_call.name + '>\n' }}
                 {%- endif %}
-                {{- '}\n</tool_call>' }}
+                {%- 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.first or (messages[loop.index0 - 1].role != "tool") %}
+        {%- if loop.previtem and loop.previtem.role != "tool" %}
             {{- '<|im_start|>user' }}
         {%- endif %}
         {{- '\n<tool_response>\n' }}
         {{- content }}
         {{- '\n</tool_response>' }}
-        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+        {%- 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
-<think>
-' }}
+    {{- '<|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 %}

ref/adapter_config.json

@@ -0,0 +1,51 @@
+{
+  "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,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "peft_version": "0.18.1",
+  "qalora_group_size": 16,
+  "r": 32,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "in_proj_qkv",
+    "in_proj_z",
+    "q_proj",
+    "k_proj",
+    "in_proj_a",
+    "up_proj",
+    "in_proj_b",
+    "out_proj",
+    "v_proj",
+    "o_proj",
+    "gate_proj",
+    "down_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

ref/adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:70ffdd72bab7a4b71e214dade0a0e64ab3b2f01b34649c3fffc11ecf367e6e22
+size 173181568

tokenizer_config.json

@@ -20,10 +20,8 @@
     "vision_bos_token": "<|vision_start|>",
     "vision_eos_token": "<|vision_end|>"
   },
-  "pad_token": "<|vision_pad|>",
-  "padding_side": "right",
+  "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+",
-  "processor_class": "Qwen3VLProcessor",
   "split_special_tokens": false,
   "tokenizer_class": "TokenizersBackend",
   "unk_token": null,