96 lines
4.0 KiB
Markdown
96 lines
4.0 KiB
Markdown
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---
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base_model:
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- mshojaei77/Gemma-2-2b-fa
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library_name: transformers
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tags:
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- mergekit
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- merge
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license: gemma
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datasets:
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- mshojaei77/Persian_sft
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language:
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- fa
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---
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# Persian Gemma 2b (v2)
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This repository hosts **Persian Gemma 2b v2**, an optimized version of the initial Persian Gemma 2b model. This version has undergone further experimental improvements through techniques like **self-merging** to enhance its performance and efficiency for Persian language conversational tasks.
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This model builds upon the foundation of Google's Gemma-2-2b-it and the initial fine-tuning efforts of `mshojaei77/Gemma-2b-fa`.
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## Key Improvements in v2
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* **Optimized Performance:** This version incorporates techniques to improve the model's performance in generating Persian text and engaging in conversations.
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* **Self-Merged:** The model has been merged with itself, potentially leading to a more robust and coherent representation.
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**Important Note:** This is still an **experimental model** and is under active development. While optimizations have been applied, it's crucial to understand that it retains the limitations inherent in a 2 billion parameter model and the early-stage nature of this project. **Output quality may vary, and critical evaluation is still necessary.**
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## How to Use
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You can use this model just like the original `mshojaei77/Gemma-2b-fa`, using the `transformers` library and the `pipeline`.
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```python
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import torch
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from transformers import pipeline
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# Initialize the text generation pipeline
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pipe = pipeline(
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"text-generation",
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model="mshojaei77/gemma-2-2b-fa-v2",
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model_kwargs={"torch_dtype": torch.bfloat16},
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device="cuda", # Or "mps" for Macs with Apple Silicon
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)
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# Prepare input messages (using the gemma chat template implicitly)
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messages = [
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{"role": "user", "content": "سلام چطوری؟"},
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]
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# Generate a response with a maximum of 512 new tokens
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outputs = pipe(messages, max_new_tokens=512, chat_template="gemma") # Explicitly using chat_template for clarity
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assistant_response = outputs[0]["generated_text"][-1]["content"].strip()
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print(assistant_response)
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# Example Output (Illustrative - Output quality may vary significantly):
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# سلام! من خوبم، ممنون. شما چطوری؟ 😊
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```
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**Key Usage Notes:**
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* **`model="mshojaei77/gemma-2-2b-fa-v2"`:** Make sure to specify the correct model name (`v2`) in your code.
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* **`chat_template="gemma"`:** Continue to use the `gemma` chat template for proper formatting.
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* **Experimental Nature:** Expect variable output quality. This is still an experimental model.
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## Model Details (v2)
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* **Base Model:** google/gemma-2-2b-it
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* **Previous Version:** mshojaei77/Gemma-2b-fa
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* **Optimization Techniques:** Self-Merging, Further Optimization.
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* **Architecture:** Gemma2ForCausalLM (same as base model)
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* **Model Size:** 2 billion parameters
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## Intended Use
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This model is intended for:
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* **Research and Experimentation:** Exploring the impact of Self-Merging techniques on Persian Gemma models.
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* **Educational Purposes:** Demonstrating advanced fine-tuning and optimization methods.
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* **Community Development:** Contributing to the growing ecosystem of Persian language models.
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* **Prototyping (with caution):** For early-stage prototyping, acknowledging its experimental nature.
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## Limitations
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While optimized, this model still has limitations:
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* **Experimental Stage:** Under ongoing development and refinement.
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* **2b Parameter Model:** Performance is limited by the model size compared to larger models.
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* **Variable Output Quality:** Output quality can still be inconsistent and require careful evaluation.
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* **Potential for Imperfections:** May still exhibit issues like fluency problems, factual inaccuracies, or biases.
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**Use this model responsibly and be aware of its experimental nature.**
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**Citation:**
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If you use this model in your research or applications, please cite it using the following DOI: [10.57967/hf/4772](https://doi.org/10.57967/hf/4772)
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