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| title: README |
| emoji: π |
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| colorTo: blue |
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| # Persian-llm-fibonacci-1-7b-chat.P1_0 π |
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| ## Description π |
| The **Persian-llm-fibonacci-1-7b-chat.P1_0** is a **1.7 billion parameter language model (LLM)** specifically designed for **Persian-language chat and text interactions**. Developed as part of the **FibonacciAI** project, this model is optimized to generate fluent and natural Persian text, making it ideal for conversational AI applications. |
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| Built on advanced language model architectures (e.g., GPT), it excels in tasks like chat, content generation, question answering, and more. π |
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| ## Use Cases π‘ |
| - **Chatbots**: Create intelligent Persian-language chatbots. π€ |
| - **Content Generation**: Generate creative and contextually relevant Persian text. π |
| - **Question Answering**: Provide natural and accurate answers to user queries. β |
| - **Machine Translation**: Translate text to and from Persian. π |
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| ## How to Use π οΈ |
| To use this model, you can leverage the `transformers` library. Here's a quick example: |
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| ```python |
| from transformers import AutoModelForCausalLM, AutoTokenizer |
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| # Load the model and tokenizer |
| model_name = "fibonacciai/Persian-llm-fibonacci-1-7b-chat.P1_0" |
| model = AutoModelForCausalLM.from_pretrained(model_name) |
| tokenizer = AutoTokenizer.from_pretrained(model_name) |
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| # Generate a response to an input text |
| input_text = "Ψ³ΩΨ§Ω
Ψ ΪΨ·ΩΨ±ΫΨ" |
| inputs = tokenizer(input_text, return_tensors="pt") |
| outputs = model.generate(**inputs, max_length=50) |
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| # Decode the output to text |
| response = tokenizer.decode(outputs[0], skip_special_tokens=True) |
| print(response) |