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)