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.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
+checkpoint-1/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+checkpoint-2/tokenizer.json filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

.ipynb_checkpoints/README-checkpoint.md

@@ -0,0 +1,74 @@
+---
+library_name: peft
+license: apache-2.0
+base_model: Qwen/Qwen2.5-7B-Instruct
+tags:
+- axolotl
+- lora
+- transformers
+- qwen
+- fine-tuning
+- text-generation
+datasets:
+- private/local  # تم استخدام بيانات تدريب محلية غير منشورة
+pipeline_tag: text-generation
+model-index:
+- name: thoth_text_v3
+  results: []
+---
+
+[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200"/>](https://github.com/axolotl-ai-cloud/axolotl)
+
+# 🧠 Thoth Text v3
+
+نموذج **Thoth Text v3** هو إصدار مطوّر من **Qwen/Qwen2.5-7B-Instruct**، تم تدريبه باستخدام أسلوب **LoRA fine-tuning** عبر مكتبة **Axolotl**، على بيانات نصية عربية تم إعدادها محليًا (غير منشورة).
+
+---
+
+## 📋 معلومات أساسية
+
+- **Base model:** [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct)  
+- **Previous adapters:**  
+  - [injazsmart/thoth_text](https://huggingface.co/injazsmart/thoth_text)  
+  - [injazsmart/thoth_text_v2](https://huggingface.co/injazsmart/thoth_text_v2)  
+- **Current version:** `thoth_text_v3`  
+- **Framework:** Axolotl + PEFT + Transformers  
+- **Hardware:** 8-bit training على GPU واحد  
+
+---
+
+## ⚙️ إعدادات التدريب (config.yaml)
+
+```yaml
+adapter: lora
+base_model: Qwen/Qwen2.5-7B-Instruct
+bf16: auto
+
+lora_model_dir: injazsmart/thoth_text_v2
+
+datasets:
+  - path: ./data/injaz.json
+    type: alpaca
+
+sequence_len: 4096
+micro_batch_size: 16
+gradient_accumulation_steps: 1
+num_epochs: 2
+learning_rate: 0.0001
+optimizer: adamw_bnb_8bit
+
+load_in_8bit: true
+lora_r: 8
+lora_alpha: 16
+lora_dropout: 0.05
+lora_target_modules:
+  - q_proj
+  - v_proj
+  - k_proj
+  - o_proj
+  - gate_proj
+  - down_proj
+  - up_proj
+
+train_on_inputs: false
+output_dir: ./outputs/thoth_text_v3

README.md

@@ -1,3 +1,74 @@
----
-license: apache-2.0
----
+---
+library_name: peft
+license: apache-2.0
+base_model: Qwen/Qwen2.5-7B-Instruct
+tags:
+- axolotl
+- lora
+- transformers
+- qwen
+- fine-tuning
+- text-generation
+datasets:
+- private/local  # تم استخدام بيانات تدريب محلية غير منشورة
+pipeline_tag: text-generation
+model-index:
+- name: thoth_text_v3
+  results: []
+---
+
+[<img src="https://raw.githubusercontent.com/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200"/>](https://github.com/axolotl-ai-cloud/axolotl)
+
+# 🧠 Thoth Text v3
+
+نموذج **Thoth Text v3** هو إصدار مطوّر من **Qwen/Qwen2.5-7B-Instruct**، تم تدريبه باستخدام أسلوب **LoRA fine-tuning** عبر مكتبة **Axolotl**، على بيانات نصية عربية تم إعدادها محليًا (غير منشورة).
+
+---
+
+## 📋 معلومات أساسية
+
+- **Base model:** [Qwen/Qwen2.5-7B-Instruct](https://huggingface.co/Qwen/Qwen2.5-7B-Instruct)  
+- **Previous adapters:**  
+  - [injazsmart/thoth_text](https://huggingface.co/injazsmart/thoth_text)  
+  - [injazsmart/thoth_text_v2](https://huggingface.co/injazsmart/thoth_text_v2)  
+- **Current version:** `thoth_text_v3`  
+- **Framework:** Axolotl + PEFT + Transformers  
+- **Hardware:** 8-bit training على GPU واحد  
+
+---
+
+## ⚙️ إعدادات التدريب (config.yaml)
+
+```yaml
+adapter: lora
+base_model: Qwen/Qwen2.5-7B-Instruct
+bf16: auto
+
+lora_model_dir: injazsmart/thoth_text_v2
+
+datasets:
+  - path: ./data/injaz.json
+    type: alpaca
+
+sequence_len: 4096
+micro_batch_size: 16
+gradient_accumulation_steps: 1
+num_epochs: 2
+learning_rate: 0.0001
+optimizer: adamw_bnb_8bit
+
+load_in_8bit: true
+lora_r: 8
+lora_alpha: 16
+lora_dropout: 0.05
+lora_target_modules:
+  - q_proj
+  - v_proj
+  - k_proj
+  - o_proj
+  - gate_proj
+  - down_proj
+  - up_proj
+
+train_on_inputs: false
+output_dir: ./outputs/thoth_text_v3

adapter_config.json

@@ -0,0 +1,42 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "Qwen/Qwen2.5-7B-Instruct",
+  "bias": "none",
+  "corda_config": null,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": null,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 16,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "qalora_group_size": 16,
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "k_proj",
+    "q_proj",
+    "o_proj",
+    "gate_proj",
+    "up_proj",
+    "down_proj",
+    "v_proj"
+  ],
+  "target_parameters": [],
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e708c0542480b550987d9a38d8074c28c640de4197044be04233000198ce04b1
+size 80792096

added_tokens.json

@@ -0,0 +1,24 @@
+{
+  "</tool_call>": 151658,
+  "<tool_call>": 151657,
+  "<|box_end|>": 151649,
+  "<|box_start|>": 151648,
+  "<|endoftext|>": 151643,
+  "<|file_sep|>": 151664,
+  "<|fim_middle|>": 151660,
+  "<|fim_pad|>": 151662,
+  "<|fim_prefix|>": 151659,
+  "<|fim_suffix|>": 151661,
+  "<|im_end|>": 151645,
+  "<|im_start|>": 151644,
+  "<|image_pad|>": 151655,
+  "<|object_ref_end|>": 151647,
+  "<|object_ref_start|>": 151646,
+  "<|quad_end|>": 151651,
+  "<|quad_start|>": 151650,
+  "<|repo_name|>": 151663,
+  "<|video_pad|>": 151656,
+  "<|vision_end|>": 151653,
+  "<|vision_pad|>": 151654,
+  "<|vision_start|>": 151652
+}

chat_template.jinja

@@ -0,0 +1,54 @@
+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- messages[0]['content'] }}
+    {%- else %}
+        {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
+    {%- endif %}
+    {{- "\n\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>" }}
+    {%- 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" }}
+{%- else %}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
+    {%- else %}
+        {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- for message in messages %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
+        {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {{- '<|im_start|>' + message.role }}
+        {%- if message.content %}
+            {{- '\n' + message.content }}
+        {%- endif %}
+        {%- for tool_call in message.tool_calls %}
+            {%- if tool_call.function is defined %}
+                {%- set tool_call = tool_call.function %}
+            {%- endif %}
+            {{- '\n<tool_call>\n{"name": "' }}
+            {{- tool_call.name }}
+            {{- '", "arguments": ' }}
+            {{- tool_call.arguments | tojson }}
+            {{- '}\n</tool_call>' }}
+        {%- endfor %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- message.content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+{%- endif %}

checkpoint-1/README.md

@@ -0,0 +1,208 @@
+---
+base_model: Qwen/Qwen2.5-7B-Instruct
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- axolotl
+- base_model:adapter:Qwen/Qwen2.5-7B-Instruct
+- lora
+- transformers
+---
+
+# 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
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- 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
+
+### 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]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.17.1

checkpoint-1/adapter_config.json

@@ -0,0 +1,42 @@
+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "Qwen/Qwen2.5-7B-Instruct",
+  "bias": "none",
+  "corda_config": null,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": null,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 16,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "qalora_group_size": 16,
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "k_proj",
+    "q_proj",
+    "o_proj",
+    "gate_proj",
+    "up_proj",
+    "down_proj",
+    "v_proj"
+  ],
+  "target_parameters": [],
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

checkpoint-1/adapter_model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:201d16b9a6a79b7841efdd250aebe0075573370cee7123d9eff11f1d4a91f5c3
+size 80792096

checkpoint-1/added_tokens.json

@@ -0,0 +1,24 @@
+{
+  "</tool_call>": 151658,
+  "<tool_call>": 151657,
+  "<|box_end|>": 151649,
+  "<|box_start|>": 151648,
+  "<|endoftext|>": 151643,
+  "<|file_sep|>": 151664,
+  "<|fim_middle|>": 151660,
+  "<|fim_pad|>": 151662,
+  "<|fim_prefix|>": 151659,
+  "<|fim_suffix|>": 151661,
+  "<|im_end|>": 151645,
+  "<|im_start|>": 151644,
+  "<|image_pad|>": 151655,
+  "<|object_ref_end|>": 151647,
+  "<|object_ref_start|>": 151646,
+  "<|quad_end|>": 151651,
+  "<|quad_start|>": 151650,
+  "<|repo_name|>": 151663,
+  "<|video_pad|>": 151656,
+  "<|vision_end|>": 151653,
+  "<|vision_pad|>": 151654,
+  "<|vision_start|>": 151652
+}

checkpoint-1/chat_template.jinja

@@ -0,0 +1,54 @@
+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- messages[0]['content'] }}
+    {%- else %}
+        {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
+    {%- endif %}
+    {{- "\n\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>" }}
+    {%- 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" }}
+{%- else %}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
+    {%- else %}
+        {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- for message in messages %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
+        {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {{- '<|im_start|>' + message.role }}
+        {%- if message.content %}
+            {{- '\n' + message.content }}
+        {%- endif %}
+        {%- for tool_call in message.tool_calls %}
+            {%- if tool_call.function is defined %}
+                {%- set tool_call = tool_call.function %}
+            {%- endif %}
+            {{- '\n<tool_call>\n{"name": "' }}
+            {{- tool_call.name }}
+            {{- '", "arguments": ' }}
+            {{- tool_call.arguments | tojson }}
+            {{- '}\n</tool_call>' }}
+        {%- endfor %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- message.content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+{%- endif %}

checkpoint-1/optimizer.pt

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+oid sha256:235bf274d962fc788bc55c53c6d376d874c4122dfd07f62cfdde5c181e510a15
+size 41460101

checkpoint-1/rng_state.pth

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+oid sha256:fe6be4449242303cee0dedd9f10f3e75e569b1e740c759a33f59510ae1322edc
+size 14645

checkpoint-1/scheduler.pt

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+version https://git-lfs.github.com/spec/v1
+oid sha256:883e3fd7e61d16e300bd860ddda442b28edad26d6c9e602eafcc4d28fae76ea8
+size 1465

checkpoint-1/special_tokens_map.json

@@ -0,0 +1,31 @@
+{
+  "additional_special_tokens": [
+    "<|im_start|>",
+    "<|im_end|>",
+    "<|object_ref_start|>",
+    "<|object_ref_end|>",
+    "<|box_start|>",
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checkpoint-1/tokenizer.json

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+size 11421896

checkpoint-1/tokenizer_config.json

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+    "<|vision_pad|>",
+    "<|image_pad|>",
+    "<|video_pad|>"
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+}

checkpoint-1/trainer_state.json

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+  "best_metric": null,
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+      "memory/max_allocated (GiB)": 22.98,
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+}

checkpoint-1/training_args.bin

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checkpoint-2/README.md

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+---
+base_model: Qwen/Qwen2.5-7B-Instruct
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- axolotl
+- base_model:adapter:Qwen/Qwen2.5-7B-Instruct
+- lora
+- transformers
+---
+
+# 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
+
+<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+
+[More Information Needed]
+
+### Downstream Use [optional]
+
+<!-- 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
+
+### 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]
+
+## Technical Specifications [optional]
+
+### Model Architecture and Objective
+
+[More Information Needed]
+
+### Compute Infrastructure
+
+[More Information Needed]
+
+#### Hardware
+
+[More Information Needed]
+
+#### Software
+
+[More Information Needed]
+
+## Citation [optional]
+
+<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
+
+**BibTeX:**
+
+[More Information Needed]
+
+**APA:**
+
+[More Information Needed]
+
+## Glossary [optional]
+
+<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
+
+[More Information Needed]
+
+## More Information [optional]
+
+[More Information Needed]
+
+## Model Card Authors [optional]
+
+[More Information Needed]
+
+## Model Card Contact
+
+[More Information Needed]
+### Framework versions
+
+- PEFT 0.17.1

checkpoint-2/adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "Qwen/Qwen2.5-7B-Instruct",
+  "bias": "none",
+  "corda_config": null,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": null,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 16,
+  "lora_bias": false,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "qalora_group_size": 16,
+  "r": 8,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
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+    "q_proj",
+    "o_proj",
+    "gate_proj",
+    "up_proj",
+    "down_proj",
+    "v_proj"
+  ],
+  "target_parameters": [],
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

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checkpoint-2/added_tokens.json

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+{
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+  "<tool_call>": 151657,
+  "<|box_end|>": 151649,
+  "<|box_start|>": 151648,
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+  "<|vision_end|>": 151653,
+  "<|vision_pad|>": 151654,
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+}

checkpoint-2/chat_template.jinja

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+{%- if tools %}
+    {{- '<|im_start|>system\n' }}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- messages[0]['content'] }}
+    {%- else %}
+        {{- 'You are Qwen, created by Alibaba Cloud. You are a helpful assistant.' }}
+    {%- endif %}
+    {{- "\n\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>" }}
+    {%- 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" }}
+{%- else %}
+    {%- if messages[0]['role'] == 'system' %}
+        {{- '<|im_start|>system\n' + messages[0]['content'] + '<|im_end|>\n' }}
+    {%- else %}
+        {{- '<|im_start|>system\nYou are Qwen, created by Alibaba Cloud. You are a helpful assistant.<|im_end|>\n' }}
+    {%- endif %}
+{%- endif %}
+{%- for message in messages %}
+    {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
+        {{- '<|im_start|>' + message.role + '\n' + message.content + '<|im_end|>' + '\n' }}
+    {%- elif message.role == "assistant" %}
+        {{- '<|im_start|>' + message.role }}
+        {%- if message.content %}
+            {{- '\n' + message.content }}
+        {%- endif %}
+        {%- for tool_call in message.tool_calls %}
+            {%- if tool_call.function is defined %}
+                {%- set tool_call = tool_call.function %}
+            {%- endif %}
+            {{- '\n<tool_call>\n{"name": "' }}
+            {{- tool_call.name }}
+            {{- '", "arguments": ' }}
+            {{- tool_call.arguments | tojson }}
+            {{- '}\n</tool_call>' }}
+        {%- endfor %}
+        {{- '<|im_end|>\n' }}
+    {%- elif message.role == "tool" %}
+        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
+            {{- '<|im_start|>user' }}
+        {%- endif %}
+        {{- '\n<tool_response>\n' }}
+        {{- message.content }}
+        {{- '\n</tool_response>' }}
+        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
+            {{- '<|im_end|>\n' }}
+        {%- endif %}
+    {%- endif %}
+{%- endfor %}
+{%- if add_generation_prompt %}
+    {{- '<|im_start|>assistant\n' }}
+{%- endif %}

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+    "lstrip": false,
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+    "single_word": false
+  }
+}

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checkpoint-2/trainer_state.json

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checkpoint-2/training_args.bin

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config.json

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+  "architectures": [
+    "Qwen2ForCausalLM"
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+  "dtype": "bfloat16",
+  "eos_token_id": 151645,
+  "hidden_act": "silu",
+  "hidden_size": 3584,
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+  "intermediate_size": 18944,
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+    "bnb_4bit_quant_type": "fp4",
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+  "vocab_size": 152064
+}

debug.log

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+[2025-10-22 17:36:09,304] [DEBUG] [axolotl.utils.config.resolve_dtype:66] [PID:1768] bf16 support detected, enabling for this configuration.
+[2025-10-22 17:36:09,599] [DEBUG] [axolotl.utils.config.log_gpu_memory_usage:127] [PID:1768] baseline 0.000GB ()
+[2025-10-22 17:36:09,602] [INFO] [axolotl.cli.config.load_cfg:248] [PID:1768] config:
+{
+  "activation_offloading": false,
+  "adapter": "lora",
+  "axolotl_config_path": "config.yaml",
+  "base_model": "Qwen/Qwen2.5-7B-Instruct",
+  "base_model_config": "Qwen/Qwen2.5-7B-Instruct",
+  "batch_size": 16,
+  "bf16": true,
+  "capabilities": {
+    "bf16": true,
+    "compute_capability": "sm_90",
+    "fp8": false,
+    "n_gpu": 1,
+    "n_node": 1
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+  "dataloader_pin_memory": true,
+  "dataloader_prefetch_factor": 256,
+  "dataset_processes": 16,
+  "datasets": [
+    {
+      "message_property_mappings": {
+        "content": "content",
+        "role": "role"
+      },
+      "path": "/workspace/fine-tuning/data/injaz.json",
+      "trust_remote_code": false,
+      "type": "alpaca"
+    }
+  ],
+  "ddp": false,
+  "device": "cuda:0",
+  "dion_rank_fraction": 1.0,
+  "dion_rank_multiple_of": 1,
+  "env_capabilities": {
+    "torch_version": "2.7.1"
+  },
+  "eval_batch_size": 16,
+  "eval_causal_lm_metrics": [
+    "sacrebleu",
+    "comet",
+    "ter",
+    "chrf"
+  ],
+  "eval_max_new_tokens": 128,
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+  "fp16": false,
+  "gradient_accumulation_steps": 1,
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+  "learning_rate": 0.0001,
+  "lisa_layers_attribute": "model.layers",
+  "load_best_model_at_end": false,
+  "load_in_4bit": false,
+  "load_in_8bit": true,
+  "local_rank": 0,
+  "lora_alpha": 16,
+  "lora_dropout": 0.05,
+  "lora_model_dir": "injazsmart/thoth_text_v2",
+  "lora_r": 8,
+  "lora_target_modules": [
+    "q_proj",
+    "v_proj",
+    "k_proj",
+    "o_proj",
+    "gate_proj",
+    "down_proj",
+    "up_proj"
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+  "loraplus_lr_embedding": 1e-06,
+  "lr_scheduler": "cosine",
+  "mean_resizing_embeddings": false,
+  "micro_batch_size": 16,
+  "model_config_type": "qwen2",
+  "num_epochs": 2.0,
+  "optimizer": "adamw_bnb_8bit",
+  "output_dir": "./outputs/thoth_text_v3",
+  "pretrain_multipack_attn": true,
+  "profiler_steps_start": 0,
+  "qlora_sharded_model_loading": false,
+  "ray_num_workers": 1,
+  "resources_per_worker": {
+    "GPU": 1
+  },
+  "sample_packing_bin_size": 200,
+  "sample_packing_group_size": 100000,
+  "save_only_model": false,
+  "save_safetensors": true,
+  "sequence_len": 4096,
+  "shuffle_before_merging_datasets": false,
+  "shuffle_merged_datasets": true,
+  "skip_prepare_dataset": false,
+  "streaming_multipack_buffer_size": 10000,
+  "strict": false,
+  "tensor_parallel_size": 1,
+  "tiled_mlp_use_original_mlp": true,
+  "tokenizer_config": "Qwen/Qwen2.5-7B-Instruct",
+  "tokenizer_save_jinja_files": true,
+  "torch_dtype": "torch.bfloat16",
+  "train_on_inputs": false,
+  "trl": {
+    "log_completions": false,
+    "mask_truncated_completions": false,
+    "ref_model_mixup_alpha": 0.9,
+    "ref_model_sync_steps": 64,
+    "scale_rewards": true,
+    "sync_ref_model": false,
+    "use_vllm": false,
+    "vllm_server_host": "0.0.0.0",
+    "vllm_server_port": 8000
+  },
+  "use_ray": false,
+  "val_set_size": 0.0,
+  "vllm": {
+    "device": "auto",
+    "dtype": "auto",
+    "gpu_memory_utilization": 0.9,
+    "host": "0.0.0.0",
+    "port": 8000
+  },
+  "weight_decay": 0.0,
+  "world_size": 1
+}
+[2025-10-22 17:36:10,629] [DEBUG] [axolotl.loaders.tokenizer.load_tokenizer:278] [PID:1768] EOS: 151645 / <|im_end|>
+[2025-10-22 17:36:10,631] [DEBUG] [axolotl.loaders.tokenizer.load_tokenizer:279] [PID:1768] BOS: None / None
+[2025-10-22 17:36:10,633] [DEBUG] [axolotl.loaders.tokenizer.load_tokenizer:280] [PID:1768] PAD: 151643 / <|endoftext|>
+[2025-10-22 17:36:10,634] [DEBUG] [axolotl.loaders.tokenizer.load_tokenizer:281] [PID:1768] UNK: None / None
+[2025-10-22 17:36:10,635] [INFO] [axolotl.utils.data.shared.load_preprocessed_dataset:476] [PID:1768] Unable to find prepared dataset in last_run_prepared/b658425644378172b1cc57b059c9f7e7
+[2025-10-22 17:36:10,638] [INFO] [axolotl.utils.data.sft._load_raw_datasets:320] [PID:1768] Loading raw datasets...
+[2025-10-22 17:36:10,639] [WARNING] [axolotl.utils.data.sft._load_raw_datasets:322] [PID:1768] Processing datasets during training can lead to VRAM instability. Please pre-process your dataset using `axolotl preprocess path/to/config.yml`.
+[2025-10-22 17:36:10,934] [INFO] [axolotl.utils.data.wrappers.get_dataset_wrapper:87] [PID:1768] Loading dataset: /workspace/fine-tuning/data/injaz.json with base_type: alpaca and prompt_style: None
+[2025-10-22 17:36:10,936] [WARNING] [datasets.arrow_dataset.map:3100] [PID:1768] num_proc must be <= 10. Reducing num_proc to 10 for dataset of size 10.
+[2025-10-22 17:36:11,344] [INFO] [axolotl.utils.data.utils.handle_long_seq_in_dataset:218] [PID:1768] min_input_len: 84
+[2025-10-22 17:36:11,347] [INFO] [axolotl.utils.data.utils.handle_long_seq_in_dataset:220] [PID:1768] max_input_len: 120
+[2025-10-22 17:36:11,350] [WARNING] [datasets.arrow_dataset.map:3100] [PID:1768] num_proc must be <= 10. Reducing num_proc to 10 for dataset of size 10.
+
+
+[2025-10-22 17:36:12,409] [DEBUG] [axolotl.utils.trainer.calculate_total_num_steps:404] [PID:1768] total_num_tokens: 1_010
+[2025-10-22 17:36:12,419] [DEBUG] [axolotl.utils.trainer.calculate_total_num_steps:422] [PID:1768] `total_supervised_tokens: 452`
+[2025-10-22 17:36:12,421] [DEBUG] [axolotl.utils.trainer.calculate_total_num_steps:520] [PID:1768] total_num_steps: 2
+[2025-10-22 17:36:12,423] [INFO] [axolotl.utils.data.sft._prepare_standard_dataset:121] [PID:1768] Maximum number of steps set at 2
+[2025-10-22 17:36:12,470] [DEBUG] [axolotl.train.setup_model_and_tokenizer:65] [PID:1768] Loading tokenizer... Qwen/Qwen2.5-7B-Instruct
+[2025-10-22 17:36:13,242] [DEBUG] [axolotl.loaders.tokenizer.load_tokenizer:278] [PID:1768] EOS: 151645 / <|im_end|>
+[2025-10-22 17:36:13,244] [DEBUG] [axolotl.loaders.tokenizer.load_tokenizer:279] [PID:1768] BOS: None / None
+[2025-10-22 17:36:13,244] [DEBUG] [axolotl.loaders.tokenizer.load_tokenizer:280] [PID:1768] PAD: 151643 / <|endoftext|>
+[2025-10-22 17:36:13,246] [DEBUG] [axolotl.loaders.tokenizer.load_tokenizer:281] [PID:1768] UNK: None / None
+[2025-10-22 17:36:13,248] [DEBUG] [axolotl.train.setup_model_and_tokenizer:74] [PID:1768] Loading model
+[2025-10-22 17:36:13,447] [DEBUG] [axolotl.monkeypatch.transformers.trainer_loss_calc.patch_evaluation_loop:87] [PID:1768] Patched Trainer.evaluation_loop with nanmean loss calculation
+[2025-10-22 17:36:13,451] [DEBUG] [axolotl.monkeypatch.transformers.trainer_loss_calc.patch_maybe_log_save_evaluate:138] [PID:1768] Patched Trainer._maybe_log_save_evaluate with nanmean loss calculation
+
+[2025-10-22 17:36:36,036] [INFO] [axolotl.loaders.model._prepare_model_for_quantization:863] [PID:1768] converting PEFT model w/ prepare_model_for_kbit_training
+[2025-10-22 17:36:36,040] [INFO] [axolotl.loaders.model._configure_embedding_dtypes:345] [PID:1768] Converting modules to torch.bfloat16
+[2025-10-22 17:36:36,044] [DEBUG] [axolotl.loaders.model.log_gpu_memory_usage:127] [PID:1768] Memory usage after model load 11.676GB (+11.676GB allocated, +13.172GB reserved)
+[2025-10-22 17:36:36,047] [DEBUG] [axolotl.loaders.adapter.load_lora:143] [PID:1768] Loading pretrained PEFT - LoRA
+
+
+trainable params: 20,185,088 || all params: 7,635,801,600 || trainable%: 0.2643
+[2025-10-22 17:36:41,269] [DEBUG] [axolotl.loaders.model.log_gpu_memory_usage:127] [PID:1768] after adapters 8.642GB (+8.642GB allocated, +13.324GB reserved)
+[2025-10-22 17:36:48,570] [INFO] [axolotl.train.save_initial_configs:398] [PID:1768] Pre-saving adapter config to ./outputs/thoth_text_v3...
+[2025-10-22 17:36:48,596] [INFO] [axolotl.train.save_initial_configs:402] [PID:1768] Pre-saving tokenizer to ./outputs/thoth_text_v3...
+[2025-10-22 17:36:49,249] [INFO] [axolotl.train.save_initial_configs:407] [PID:1768] Pre-saving model config to ./outputs/thoth_text_v3...
+[2025-10-22 17:36:49,268] [INFO] [axolotl.train.execute_training:196] [PID:1768] Starting trainer...
+
  0%|                                                                                                                              | 0/2 [00:00<?, ?it/s][2025-10-22 17:36:50,364] [WARNING] [py.warnings._showwarnmsg:110] [PID:1768] /root/miniconda3/envs/py3.11/lib/python3.11/site-packages/bitsandbytes/autograd/_functions.py:186: UserWarning: MatMul8bitLt: inputs will be cast from torch.bfloat16 to float16 during quantization
+  warnings.warn(f"MatMul8bitLt: inputs will be cast from {A.dtype} to float16 during quantization")
+
+
 50%|███████████████████████████████████████████████████████████                                                           | 1/2 [00:01<00:01,  1.57s/it]
                                                                                                                                                         
+
 50%|███████████████████████████████████████████████████████████                                                           | 1/2 [00:01<00:01,  1.57s/it][2025-10-22 17:36:51,326] [INFO] [axolotl.core.trainers.base._save:671] [PID:1768] Saving model checkpoint to ./outputs/thoth_text_v3/checkpoint-1
+[2025-10-22 17:36:54,243] [WARNING] [py.warnings._showwarnmsg:110] [PID:1768] /root/miniconda3/envs/py3.11/lib/python3.11/site-packages/bitsandbytes/autograd/_functions.py:186: UserWarning: MatMul8bitLt: inputs will be cast from torch.bfloat16 to float16 during quantization
+  warnings.warn(f"MatMul8bitLt: inputs will be cast from {A.dtype} to float16 during quantization")
+
+
                                                                                                                                                         
+
+
                                                                                                                                                         
+
+[2025-10-22 17:36:57,557] [INFO] [axolotl.train.save_trained_model:218] [PID:1768] Training completed! Saving trained model to ./outputs/thoth_text_v3.
+[2025-10-22 17:36:58,688] [INFO] [axolotl.train.save_trained_model:336] [PID:1768] Model successfully saved to ./outputs/thoth_text_v3

special_tokens_map.json

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+size 11421896

tokenizer_config.json

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