tasal9
/

pashto-base-bloom

@@ -9,396 +9,85 @@ tags:
 - pashto
 - lightweight
 - language-model
-- zamai
 base_model: bigscience/bloomz-560m
 pipeline_tag: text-generation
 datasets:
 - tasal9/Pashto-Dataset-Creating-Dataset
-widget:
-- text: "Hello, how can I help you today?"
-  example_title: "English Greeting"
-- text: "سلام وروره، څنګه یاست؟"
-  example_title: "Pashto Greeting"
-model-index:
-- name: pashto-base-bloom
-  results:
-  - task:
-      type: text-generation
-      name: Text Generation
-    dataset:
-      type: custom
-      name: Pashto Educational Dataset
-    metrics:
-    - type: accuracy
-      value: 92.5
-      name: Overall Accuracy
-    - type: bleu
-      value: 0.85
-      name: BLEU Score
 ---
 # pashto-base-bloom
-<div align="center">
-  <img src="https://huggingface.co/datasets/huggingface/brand-assets/resolve/main/hf-logo.png" alt="Hugging Face" width="100"/>
-  <h2>🌟 Part of ZamAI Pro Models Strategy</h2>
-  <p><strong>BLOOM-based model fine-tuned for Pashto language tasks</strong></p>
-</div>
 ## 🌟 Model Overview
-pashto-base-bloom is an advanced AI model specifically designed for multilingual applications with specialized focus on Pashto language support. This model is part of the comprehensive **ZamAI Pro Models Strategy**, aimed at bridging language gaps and providing high-quality AI solutions for underrepresented languages.
-### 🎯 Key Features
-- 🧠 **Advanced Architecture**: Built on bigscience/bloomz-560m
-- 🌐 **Multilingual Support**: Optimized for Pashto (ps) and English (en)
 - ⚡ **High Performance**: Optimized for production deployment
-- 🔒 **Enterprise-Grade**: Secure and reliable for business use
-- 📱 **Production-Ready**: Tested and deployed in real applications
-- 🎓 **Educational Focus**: Designed for learning and cultural preservation
-## 🎯 Use Cases & Applications
-This model excels in the following scenarios:
-- **Lightweight Applications**: Advanced text generation capabilities
-- **Mobile Deployment**: Advanced text generation capabilities
-- **Quick Prototyping**: Advanced text generation capabilities
-- **Educational Tools**: Advanced text generation capabilities
-- **Resource-Constrained Environments**: Advanced text generation capabilities
-### 🌍 Real-World Applications
-- **🎓 Educational Platforms**: Powering Pashto language tutoring and learning systems
-- **📄 Business Automation**: Document processing, form analysis, and content generation
-- **🎤 Voice Applications**: Natural language understanding for voice assistants
-- **🏛️ Cultural Preservation**: Supporting Pashto language technology and digital preservation
-- **🌐 Translation Services**: Cross-lingual communication and content localization
-- **🤖 Chatbot Development**: Building intelligent conversational agents
-## 📚 Quick Start
-### 🔧 Installation
-```bash
-pip install transformers torch huggingface_hub
-```
-### 🚀 Basic Usage
 ```python
-from transformers import AutoTokenizer, AutoModelForCausalLM
-from huggingface_hub import InferenceClient
-# Method 1: Using Transformers (Local)
 tokenizer = AutoTokenizer.from_pretrained("tasal9/pashto-base-bloom")
-model = AutoModelForCausalLM.from_pretrained("tasal9/pashto-base-bloom")
-# Example text
 text = "Your input text here"
 inputs = tokenizer(text, return_tensors="pt")
-# Generate response
-with torch.no_grad():
-    outputs = model.generate(
-        **inputs,
-        max_new_tokens=200,
-        temperature=0.7,
-        top_p=0.9,
-        pad_token_id=tokenizer.eos_token_id
-    )
-response = tokenizer.decode(outputs[0], skip_special_tokens=True)
-print(response)
 ```
-### 🌐 Using Hugging Face Inference API
 ```python
 from huggingface_hub import InferenceClient
-# Initialize client
 client = InferenceClient(token="your_hf_token")
-# Generate text
 response = client.text_generation(
     model="tasal9/pashto-base-bloom",
     prompt="Your prompt here",
-    max_new_tokens=200,
-    temperature=0.7,
-    top_p=0.9
-)
-print(response)
-```
-### 🎯 Specialized Usage Examples
-#### English Query
-```python
-prompt = "Explain the importance of renewable energy in simple terms:"
-response = client.text_generation(
-    model="tasal9/pashto-base-bloom",
-    prompt=prompt,
-    max_new_tokens=250,
-    temperature=0.7
-)
-```
-#### Pashto Query
-```python
-prompt = "د بشپړ پوښتنه: د کرښنې ورانۍ د کرکټرونو په اړه تاسو څه پوه یاست؟"
-response = client.text_generation(
-    model="tasal9/pashto-base-bloom",
-    prompt=prompt,
-    max_new_tokens=250,
-    temperature=0.7
-)
-```
-## 🔧 Technical Specifications
-| Specification | Details |
-|---------------|---------|
-| **Model Type** | Text Generation |
-| **Base Model** | bigscience/bloomz-560m |
-| **Languages** | Pashto (ps), English (en) |
-| **License** | MIT |
-| **Context Length** | Variable (depends on base model) |
-| **Parameters** | Optimized for efficiency |
-| **Framework** | PyTorch, Transformers |
-| **Deployment** | HF Inference API, Local, Docker |
-## 📊 Performance Metrics
-| Metric | Score | Description |
-|--------|-------|-------------|
-| **Overall Accuracy** | 92.5% | Performance on Pashto evaluation dataset |
-| **BLEU Score** | 0.85 | Translation and generation quality |
-| **Cultural Relevance** | 95% | Appropriateness for Pashto cultural context |
-| **Response Time** | <200ms | Average inference time via API |
-| **Multilingual Score** | 89% | Cross-lingual understanding capability |
-| **Coherence Score** | 91% | Logical flow and consistency |
-## 🌐 Interactive Demo
-Try the model instantly with our Gradio demos:
-### 🎯 Live Demos
-- **[Complete Suite Demo](https://huggingface.co/spaces/tasal9/zamai-complete-suite)** - All models in one interface
-- **[Individual Model Demo](https://huggingface.co/spaces/tasal9/pashto-base-bloom)** - Focused interface for this model
-### 🔗 API Endpoints
-- **Inference API**: `https://api-inference.huggingface.co/models/tasal9/pashto-base-bloom`
-- **Model Hub**: `https://huggingface.co/tasal9/pashto-base-bloom`
-## 🚀 Deployment Options
-### 1. 🌐 Hugging Face Inference API (Recommended)
-```python
-from huggingface_hub import InferenceClient
-client = InferenceClient(token="your_token")
-response = client.text_generation(model="tasal9/pashto-base-bloom", prompt="Your prompt")
-```
-### 2. 🖥️ Local Deployment
-```bash
-# Clone the model
-git clone https://huggingface.co/tasal9/pashto-base-bloom
-cd pashto-base-bloom
-# Run with Python
-python -c "
-from transformers import pipeline
-pipe = pipeline('text-generation', model='.')
-print(pipe('Your prompt here'))
-"
-```
-### 3. 🐳 Docker Deployment
-```dockerfile
-FROM python:3.9-slim
-RUN pip install transformers torch
-COPY . /app
-WORKDIR /app
-CMD ["python", "app.py"]
-```
-### 4. ☁️ Cloud Deployment
-Compatible with major cloud platforms:
-- **AWS SageMaker**
-- **Google Cloud AI Platform**
-- **Azure Machine Learning**
-- **Hugging Face Spaces**
-## 📈 Model Training & Fine-tuning
-### 🎯 Training Data
-- **Primary Dataset**: Custom Pashto educational content
-- **Secondary Data**: Multilingual parallel corpora
-- **Domain Focus**: Educational, cultural, and conversational content
-- **Quality Assurance**: Human-reviewed and culturally validated
-### 🔧 Fine-tuning Process
-```python
-from transformers import TrainingArguments, Trainer
-# Example fine-tuning setup
-training_args = TrainingArguments(
-    output_dir="./results",
-    num_train_epochs=3,
-    per_device_train_batch_size=4,
-    per_device_eval_batch_size=4,
-    warmup_steps=500,
-    weight_decay=0.01,
-    logging_dir="./logs",
-)
-# Initialize trainer
-trainer = Trainer(
-    model=model,
-    args=training_args,
-    train_dataset=train_dataset,
-    eval_dataset=eval_dataset,
 )
-# Start training
-trainer.train()
 ```
-## 🤝 Community & Contributions
-### 📝 Contributing
-We welcome contributions to improve this model:
-1. **Data Contributions**: Share high-quality Pashto language datasets
-2. **Model Improvements**: Suggest architectural enhancements or optimizations
-3. **Use Case Development**: Build applications and share success stories
-4. **Bug Reports**: Help us identify and fix issues
-5. **Documentation**: Improve guides and examples
-### 🌟 Community Projects
-- **Educational Apps**: Language learning applications
-- **Business Tools**: Document processing solutions
-- **Research**: Academic studies and papers
-- **Open Source**: Community-driven improvements
-### 📊 Usage Analytics
-- **Downloads**: Track model adoption
-- **Community Feedback**: User reviews and ratings
-- **Performance Reports**: Real-world usage statistics
-## 🔗 Related Models & Resources
-### 🤖 Other ZamAI Models
-- [**ZamAI-Mistral-7B-Pashto**](https://huggingface.co/tasal9/ZamAI-Mistral-7B-Pashto) - Educational tutor
-- [**ZamAI-Phi-3-Mini-Pashto**](https://huggingface.co/tasal9/ZamAI-Phi-3-Mini-Pashto) - Business assistant
-- [**ZamAI-Whisper-v3-Pashto**](https://huggingface.co/tasal9/ZamAI-Whisper-v3-Pashto) - Speech recognition
-- [**Multilingual-ZamAI-Embeddings**](https://huggingface.co/tasal9/Multilingual-ZamAI-Embeddings) - Text embeddings
-- [**ZamAI-LLaMA3-Pashto**](https://huggingface.co/tasal9/ZamAI-LLaMA3-Pashto) - Advanced chat
-- [**pashto-base-bloom**](https://huggingface.co/tasal9/pashto-base-bloom) - Lightweight model
-### 📚 Datasets
-- [**Pashto-Dataset-Creating-Dataset**](https://huggingface.co/datasets/tasal9/Pashto-Dataset-Creating-Dataset) - Training data
-### 🌐 Platform Links
-- **Organization**: [tasal9](https://huggingface.co/tasal9)
-- **Complete Demo**: [ZamAI Suite](https://huggingface.co/spaces/tasal9/zamai-complete-suite)
-## 📞 Support & Contact
-### 🆘 Getting Help
 - 📧 **Email**: [email protected]
 - 🌐 **Website**: [zamai.ai](https://zamai.ai)
-- 📖 **Documentation**: [docs.zamai.ai](https://docs.zamai.ai)
-- 💬 **Community Forum**: [community.zamai.ai](https://community.zamai.ai)
-- 🐙 **GitHub**: [github.com/zamai-ai](https://github.com/zamai-ai)
-### 💼 Enterprise Support
-For enterprise deployments, custom fine-tuning, or integration assistance:
-- 📧 **Enterprise**: [email protected]
-- 📞 **Phone**: +1-XXX-XXX-XXXX
-- 💼 **Consulting**: [zamai.ai/consulting](https://zamai.ai/consulting)
-## 🏷️ Citation
-If you use this model in your research or applications, please cite:
-```bibtex
-@misc{zamai-pashto-base-bloom-2024,
-  title={pashto-base-bloom: BLOOM-based model fine-tuned for Pashto language tasks},
-  author={ZamAI Team},
-  year={2024},
-  url={https://huggingface.co/tasal9/pashto-base-bloom},
-  note={ZamAI Pro Models Strategy - Multilingual AI Platform},
-  publisher={Hugging Face}
-}
-```
-### 📜 Academic Papers
-```bibtex
-@article{zamai2024multilingual,
-  title={Advancing Multilingual AI: The ZamAI Pro Models Strategy for Pashto Language Technology},
-  author={ZamAI Research Team},
-  journal={Journal of Multilingual AI},
-  year={2024},
-  volume={1},
-  pages={1--15}
-}
-```
-## 📄 License & Terms
-### 📋 License
-This model is licensed under the **MIT License**:
-- ✅ **Commercial Use**: Allowed for business applications
-- ✅ **Modification**: Can be modified and improved
-- ✅ **Distribution**: Can be redistributed
-- ✅ **Private Use**: Allowed for personal projects
-- ⚠️ **Attribution Required**: Credit must be given to ZamAI
-### 📝 Terms of Use
-1. **Responsible AI**: Use ethically and responsibly
-2. **No Harmful Content**: Do not generate harmful or offensive content
-3. **Privacy**: Respect user privacy and data protection laws
-4. **Cultural Sensitivity**: Be respectful of Pashto culture and language
-5. **Compliance**: Follow local laws and regulations
-### 🛡️ Limitations & Disclaimers
-- Model outputs should be reviewed for accuracy
-- Not suitable for critical decision-making without human oversight
-- May have biases inherited from training data
-- Performance may vary across different domains
-## 📈 Changelog & Updates
-| Version | Date | Changes |
-|---------|------|---------|
-| **v1.0** | 2025-07-05 | Initial release with enhanced Pashto support |
-| **v1.1** | TBD | Performance optimizations and bug fixes |
-| **v2.0** | TBD | Extended language support and new features |
-### 🔄 Update Schedule
-- **Monthly**: Performance monitoring and minor improvements
-- **Quarterly**: Feature updates and enhancements
-- **Annually**: Major version releases with significant improvements
 ---
-<div align="center">
-  <h3>🌟 Part of the ZamAI Pro Models Strategy</h3>
-  <p><strong>Transforming AI for Multilingual Applications</strong></p>
-  <p>
-    <a href="https://zamai.ai">🌐 Website</a> •
-    <a href="https://huggingface.co/tasal9">🤗 Models</a> •
-    <a href="https://community.zamai.ai">💬 Community</a> •
-    <a href="mailto:[email protected]">📧 Support</a>
-  </p>
-  <p><em>Last Updated: 2025-07-05 21:15:52 UTC</em></p>
-  <p><em>Model Card Version: 2.0</em></p>
-</div>

 - pashto
 - lightweight
 - language-model
 base_model: bigscience/bloomz-560m
 pipeline_tag: text-generation
 datasets:
 - tasal9/Pashto-Dataset-Creating-Dataset
 ---
 # pashto-base-bloom
+BLOOM-based model fine-tuned for Pashto language tasks
 ## 🌟 Model Overview
+This model is part of the **ZamAI Pro Models Strategy** - a comprehensive AI platform designed for multilingual applications with specialized focus on Pashto language support.
+### Key Features
+- 🧠 **Advanced AI**: Based on bigscience/bloomz-560m architecture
+- 🌐 **Multilingual**: Optimized for Pashto and English
 - ⚡ **High Performance**: Optimized for production deployment
+- 🔒 **Secure**: Enterprise-grade security and privacy
+## 📚 Usage
+### Basic Usage with Transformers
 ```python
+from transformers import AutoTokenizer, AutoModel
 tokenizer = AutoTokenizer.from_pretrained("tasal9/pashto-base-bloom")
+model = AutoModel.from_pretrained("tasal9/pashto-base-bloom")
+# Example usage
 text = "Your input text here"
 inputs = tokenizer(text, return_tensors="pt")
+outputs = model(**inputs)
 ```
+### Usage with Hugging Face Inference API
 ```python
 from huggingface_hub import InferenceClient
 client = InferenceClient(token="your_hf_token")
 response = client.text_generation(
     model="tasal9/pashto-base-bloom",
     prompt="Your prompt here",
+    max_new_tokens=200
 )
 ```
+## 🔧 Technical Details
+- **Model Type**: text-generation
+- **Base Model**: bigscience/bloomz-560m
+- **Languages**: Pashto (ps), English (en)
+- **License**: MIT
+- **Training**: Fine-tuned on Pashto educational and cultural content
+## 🚀 Applications
+This model powers:
+- **ZamAI Educational Platform**: Pashto language tutoring
+- **Business Automation**: Document processing and analysis
+- **Voice Assistants**: Natural language understanding
+- **Cultural Preservation**: Supporting Pashto language technology
+## 📞 Support
+For support and integration assistance:
 - 📧 **Email**: [email protected]
 - 🌐 **Website**: [zamai.ai](https://zamai.ai)
+- 💬 **Community**: [ZamAI Community](https://community.zamai.ai)
+## 📄 License
+Licensed under the MIT License.
 ---
+**Part of the ZamAI Pro Models Strategy - Transforming AI for Multilingual Applications** 🌟
+*Updated: 2025-07-05 21:29:16 UTC*