Initial push of CodeLLaMA Linux BugFix model with Hugging Face LFS support

.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
+*.json filter=lfs diff=lfs merge=lfs -text
+*.jsonl filter=lfs diff=lfs merge=lfs -text
+*.csv filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,3 +1,294 @@
+# Linux Kernel Anti-Pattern Detector
+
+A comprehensive tool for detecting anti-patterns and potential issues in Linux kernel code.
+
+## 🎯 Overview
+
+This project provides automated static analysis tools to identify common anti-patterns, code smells, and potential issues in Linux kernel source code. The analysis covers 7 major categories including memory management, concurrency, security vulnerabilities, and code quality issues.
+
+## 📊 Recent Analysis Results
+
+**Analysis Date:** June 29, 2025  
+**Kernel Version:** Linux 6.16-rc4  
+**Files Analyzed:** 35,588  
+**Total Issues Found:** 3,122
+
+### Issue Distribution
+- **🔴 Critical Security Issues:** 347 (11.1%)
+- **🟡 High Priority Issues:** 2,670 (85.5%)
+- **🔵 Medium Priority Issues:** 105 (3.4%)
+
+### Top Categories
+1. **Concurrency Issues:** 2,314 (74.1%) - Race conditions, deadlocks
+2. **Memory Management:** 356 (11.4%) - Memory leaks, use-after-free
+3. **Security Vulnerabilities:** 347 (11.1%) - Buffer overflows, format strings
+4. **Code Quality:** 92 (2.9%) - Magic numbers, code duplication
+
+## 🚀 Quick Start
+
+### Prerequisites
+- Python 3.8+
+- Git
+- Conda (recommended for environment management)
+
+### Setup
+```bash
+# Clone the repository
+git clone https://github.com/Mac-Huang/linux-kernel-anti-pattern-detector.git
+cd linux-kernel-anti-pattern-detector
+
+# Create and activate conda environment
+conda create -n linux-kernel-anti-pattern-detector python=3.10 -y
+conda activate linux-kernel-anti-pattern-detector
+
+# Install dependencies
+pip install -r requirements.txt
+pip install -r requirements-kernel-analysis.txt
+```
+
+### Run Analysis
+```bash
+# Full kernel analysis (clones kernel if needed)
+python tools/detectors/detector.py --clone --output data/results.json
+
+# Concurrency-specific analysis
+python scripts/analysis/concurrency_analyzer.py
+
+# View results interactively
+python scripts/reporting/view_results.py --interactive
+```
+
+## 🗃️ Dataset Building Pipeline
+
+### ✅ **Successfully Implemented**
+
+The project includes a robust dataset building pipeline for training code intelligence models on Linux kernel bug fixes.
+
+#### **Dataset Format**
+```json
+{
+  "input": {
+    "original code": "code before the patch (extracted from a known bug-fix)",
+    "instruction": "the commit message describing what this fix is"
+  },
+  "output": {
+    "diff codes": "the unified diff patch for the bug fix"
+  }
+}
+```
+
+#### **Features**
+- **🔍 Intelligent Bug Detection:** Uses keyword-based filtering to identify bug-fix commits
+- **📝 Focused Code Extraction:** Extracts relevant code context around bug fixes
+- **🔧 Diff Processing:** Parses and formats unified diff patches
+- **⚡ Parallel Processing:** Multi-threaded processing for large repositories
+- **📊 Quality Filtering:** Only includes valid C source file modifications
+
+#### **Usage**
+```bash
+# Activate environment
+conda activate detector
+
+# Build test dataset (small sample)
+cd dataset_builder
+python build_dataset_demo.py
+
+# Build full dataset (entire repository)
+# Edit TEST_MODE = False in build_dataset_demo.py
+python build_dataset_demo.py
+```
+
+#### **Output**
+- **File:** `dataset_builder/output/linux_bugfix_dataset.jsonl`
+- **Format:** JSONL (one JSON object per line)
+- **Content:** Bug-fix commits with original code, commit messages, and diff patches
+
+#### **Keywords Detected**
+- Memory issues: `leak`, `null`, `overflow`, `memory`
+- Security: `security`, `vulnerability`, `exploit`, `buffer`
+- Concurrency: `race`, `deadlock`, `lock`
+- General bugs: `fix`, `bug`, `error`, `failure`, `crash`
+
+## 📁 Project Structure
+
+```
+├── 📁 data/                    # Analysis results and logs
+├── 📁 dataset_builder/         # Dataset building pipeline
+│   ├── build_dataset.py        # Main dataset builder
+│   ├── build_dataset_demo.py   # Test dataset builder
+│   └── output/                 # Generated datasets
+├── 📁 docs/                    # Documentation
+├── 📁 reports/                 # Generated reports
+├── 📁 scripts/                 # Analysis and utility scripts
+├── 📁 src/                     # Core source code
+├── 📁 tests/                   # Test files
+├── 📁 tools/                   # Detection tools
+└── 📁 linux/                   # Kernel source (cloned)
+```
+
+See [PROJECT_STRUCTURE.md](PROJECT_STRUCTURE.md) for detailed structure information.
+
+## 📋 Available Reports
+
+### 📄 Main Reports
+- **[Complete Analysis Report](reports/Linux_Kernel_Anti_Pattern_Analysis_Report.md)** - Full technical analysis
+- **[Executive Summary](reports/Executive_Summary.md)** - High-level overview for stakeholders
+
+### 🔒 Specialized Reports
+- **[Concurrency Analysis](reports/concurrency/Concurrency_Analysis_Report.md)** - Detailed concurrency issues (2,314 issues)
+
+## 🛠️ Usage Examples
+
+### Basic Analysis
+```bash
+# Run complete analysis
+python tools/detectors/detector.py --clone --output data/results.json
+
+# Quick summary
+python scripts/utils/quick_summary.py
+
+# Interactive results viewer
+python scripts/reporting/view_results.py --interactive
+```
+
+### Specialized Analysis
+```bash
+# Concurrency issues only
+python scripts/analysis/concurrency_analyzer.py
+
+# Kernel structure analysis
+python scripts/analysis/analyze_kernel_structure.py
+```
+
+### Custom Configuration
+```bash
+# Use custom config
+python tools/detectors/detector.py --config tools/detectors/config.yaml
+
+# Analyze specific kernel path
+python tools/detectors/detector.py --kernel-path /path/to/kernel
+```
+
+## 🔍 Detection Categories
+
+### 1. Memory Management
+- Memory leaks (kmalloc without kfree)
+- Use-after-free bugs
+- Double-free issues
+- Null pointer dereferences
+
+### 2. Concurrency
+- Race conditions
+- Deadlocks
+- Missing locks
+- Double locking
+- Lock ordering violations
+
+### 3. Security
+- Buffer overflows
+- Format string vulnerabilities
+- Privilege escalation
+- Information disclosure
+
+### 4. Error Handling
+- Unchecked return values
+- Missing error handling
+- Ignored error codes
+- Wrong error propagation
+
+### 5. Performance
+- O(n²) algorithms
+- Unnecessary memory allocation
+- Inefficient data structures
+- Cache miss patterns
+
+### 6. Code Quality
+- Magic numbers
+- Hardcoded values
+- Complex functions
+- Code duplication
+
+### 7. API Usage
+- Deprecated functions
+- Wrong API usage
+- Missing parameter validation
+- Incorrect flags
+
+## 📊 Analysis Features
+
+- **Pattern-based Detection:** Regular expression matching with context awareness
+- **Parallel Processing:** Configurable concurrent analysis for performance
+- **Detailed Reporting:** JSON output with file locations and line numbers
+- **Interactive Viewer:** Browse and filter results by category and severity
+- **Code Snippet Extraction:** View actual code around detected issues
+- **Severity Classification:** Critical, High, Medium, Low priority levels
+
+## 🔧 Configuration
+
+The analysis can be customized through `tools/detectors/config.yaml`:
+
+```yaml
+detection_rules:
+  memory_management:
+    enabled: true
+    severity: "high"
+    patterns:
+      - "kmalloc.*without.*kfree"
+      - "use.*after.*free"
+    directories: ["drivers", "kernel", "mm"]
+```
+
+## 📈 Performance
+
+- **Analysis Speed:** ~11 minutes for 35,588 files
+- **Memory Usage:** Configurable limits (default: 1GB)
+- **Parallel Processing:** Up to 4 concurrent analyzers
+- **File Filtering:** Excludes generated files and build artifacts
+
+## 🤝 Contributing
+
+1. **Fork the repository**
+2. **Create a feature branch** (`git checkout -b feature/amazing-feature`)
+3. **Add your changes** following the project structure
+4. **Test your changes** (`python -m pytest tests/`)
+5. **Commit your changes** (`git commit -m 'Add amazing feature'`)
+6. **Push to the branch** (`git push origin feature/amazing-feature`)
+7. **Open a Pull Request**
+
+### Development Guidelines
+- **Analysis scripts:** Add to `scripts/analysis/`
+- **Reporting tools:** Add to `scripts/reporting/`
+- **Core detection:** Add to `src/detectors/`
+- **Configuration:** Update `tools/detectors/config.yaml`
+
+## 📚 Documentation
+
+- **[Project Structure](PROJECT_STRUCTURE.md)** - Detailed project organization
+- **[Kernel Analysis Guide](docs/kernel-analysis-guide.md)** - Comprehensive analysis guide
+- **[Concurrency Analysis](reports/concurrency/Concurrency_Analysis_Report.md)** - Concurrency-specific findings
+
+## 🐛 Known Issues
+
+- **Code snippet extraction:** Some file paths may not match due to kernel cloning method
+- **Large file handling:** Files >10MB are skipped to prevent memory issues
+- **Pattern accuracy:** Some patterns may generate false positives
+
+## 📄 License
+
+This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
+
+## 🙏 Acknowledgments
+
+- Linux kernel community for the source code
+- Static analysis research community
+- Contributors and maintainers
+
+## 📞 Contact
+
+- **Repository:** https://github.com/Mac-Huang/linux-kernel-anti-pattern-detector
+- **Issues:** Use GitHub Issues for bug reports and feature requests
+- **Discussions:** Use GitHub Discussions for questions and ideas
+
 ---
-license: apache-2.0
----
+
+*This tool is designed to help improve Linux kernel code quality by identifying potential issues early in the development process. The analysis results should be used as guidance for improvement rather than definitive assessments of code quality.* 

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chat_template.jinja

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checkpoint-1000/README.md

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+---
+base_model: codellama/CodeLLaMA-7b-Instruct-hf
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:codellama/CodeLLaMA-7b-Instruct-hf
+- 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 0.16.0

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+{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% set system_message = false %}{% endif %}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if loop.index0 == 0 and system_message != false %}{% set content = '<<SYS>>\n' + system_message + '\n<</SYS>>\n\n' + message['content'] %}{% else %}{% set content = message['content'] %}{% endif %}{% if message['role'] == 'user' %}{{ bos_token + '[INST] ' + content | trim + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ ' '  + content | trim + ' ' + eos_token }}{% endif %}{% endfor %}

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checkpoint-500/README.md

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+---
+base_model: codellama/CodeLLaMA-7b-Instruct-hf
+library_name: peft
+pipeline_tag: text-generation
+tags:
+- base_model:adapter:codellama/CodeLLaMA-7b-Instruct-hf
+- 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 0.16.0

checkpoint-500/adapter_config.json

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checkpoint-500/adapter_model.safetensors

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checkpoint-500/chat_template.jinja

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+{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% set system_message = false %}{% endif %}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if loop.index0 == 0 and system_message != false %}{% set content = '<<SYS>>\n' + system_message + '\n<</SYS>>\n\n' + message['content'] %}{% else %}{% set content = message['content'] %}{% endif %}{% if message['role'] == 'user' %}{{ bos_token + '[INST] ' + content | trim + ' [/INST]' }}{% elif message['role'] == 'assistant' %}{{ ' '  + content | trim + ' ' + eos_token }}{% endif %}{% endfor %}

checkpoint-500/optimizer.pt

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checkpoint-500/rng_state.pth

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checkpoint-500/scheduler.pt

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checkpoint-500/special_tokens_map.json

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checkpoint-500/tokenizer.json

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checkpoint-500/tokenizer_config.json

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checkpoint-500/trainer_state.json

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checkpoint-500/training_args.bin

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special_tokens_map.json

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tokenizer.json

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tokenizer_config.json

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