| Chat Model | |
| This is a custom chat model fine-tuned for conversational AI. The model is based on LLaMA architecture and is specifically designed for Arabic and English conversations. | |
| Model Details | |
| Architecture: LLaMA | |
| Task: Text Generation | |
| Language: Arabic/English | |
| License: MIT | |
| Model Size: Large | |
| Training Data: Custom conversational data | |
| Optimization: Quantized (int8) | |
| Usage | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| model = AutoModelForCausalLM.from_pretrained("gamer-to/chat-model") | |
| tokenizer = AutoTokenizer.from_pretrained("gamer-to/chat-model") | |
| # Example input | |
| input_text = "مرحبا كيف حالك؟" | |
| inputs = tokenizer(input_text, return_tensors="pt") | |
| outputs = model.generate( | |
| **inputs, | |
| max_length=256, | |
| temperature=0.7, | |
| do_sample=True, | |
| top_p=0.95 | |
| ) | |
| response = tokenizer.decode(outputs[0], skip_special_tokens=True) | |
| Inference API | |
| This model is compatible with Hugging Face's Inference API. You can use it with the following endpoint: | |
| POST https://api-inference.huggingface.co/models/gamer-to/chat-model | |
| Model Performance | |
| Optimized for conversational tasks | |
| Supports both Arabic and English | |
| Fast response times | |
| High-quality responses | |
| Requirements | |
| PyTorch | |
| Transformers | |
| CUDA (optional for GPU acceleration) |