初始化项目，由ModelHub XC社区提供模型

Model: Lyte/Gemma-3-1B-Moroccan-Instruct
Source: Original Platform

README.md

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+---
+base_model: unsloth/gemma-3-1b-it-unsloth-bnb-4bit
+tags:
+- text-generation-inference
+- transformers
+- unsloth
+- gemma3_text
+- gguf
+license: apache-2.0
+language:
+- ary
+datasets:
+- Lyte/Moroccan-QA-Extended
+pipeline_tag: text-generation
+library_name: unsloth
+---
+
+# Gemma-3-1B Moroccan Instruct (test finetune)
+
+- **Developed by:** Lyte
+- **License:** Apache-2.0
+- **Base model:** `unsloth/gemma-3-1b-it-unsloth-bnb-4bit`
+- **Dataset:** `Lyte/Moroccan-QA-Extended` (with additional English Questions -> Moroccan Darija Answers)
+- **Language:** Moroccan Arabic (Darija)
+
+## How to use in LM Studio
+
+You can easily run this model in LM Studio using the preset configuration. Click the badge below to open the model directly in LM Studio:
+
+[<img src="https://pbs.twimg.com/profile_images/1755060270173429760/4WVc54_p_400x400.jpg" alt="Open in LM Studio" width="32"/>](https://lmstudio.ai/lyte/gemma-3-moroccan)
+
+### GGUF Quants:
+
+- **Q8_0:** [gemma-3-1b-moroccan-instruct-q8_0.gguf](https://huggingface.co/Lyte/Gemma-3-1B-Moroccan-Instruct/resolve/main/gemma-3-1b-moroccan-instruct-q8_0.gguf?download=true)
+- **Q4_K_M:** [gemma-3-1b-moroccan-instruct-q4_k_m.gguf](https://huggingface.co/Lyte/Gemma-3-1B-Moroccan-Instruct/resolve/main/gemma-3-1b-moroccan-instruct-q4_k_m.gguf?download=true)
+
+
+## Inference Example
+
+Here is an example of the model's output in LM Studio, answering a question about Newton's law of universal gravitation in Moroccan Darija.
+
+### Q: what is the capital of France?
+![Inference Example 1](https://huggingface.co/Lyte/Gemma-3-1B-Moroccan-Instruct/resolve/main/capital.png)
+
+### Q: شرح ليا كيفاش الجادبية كتخدم؟
+![Inference Example 2](https://huggingface.co/Lyte/Gemma-3-1B-Moroccan-Instruct/resolve/main/gravity.png)
+
+### Inference Settings:
+
+![Inference Settings](https://huggingface.co/Lyte/Gemma-3-1B-Moroccan-Instruct/resolve/main/sampling.png)
+
+
+---
+
+## Training Details
+
+- **Max Length:** 1024 tokens
+- **Epochs:** 3
+- **Total Steps:** 843
+- **Batch size:** 2 (per device)
+- **Gradient Accumulation:** 4 (Total effective batch size: 16)
+- **Learning rate:** 2e-4
+- **Optimizer:** 8-bit AdamW
+- **Scheduler:** Linear
+- **Weight decay:** 0.01
+- **Seed:** 3407
+- **Num of Examples:** 4,495
+- **Trainable Parameters:** 52.18M (4.96%)
+- **Training Time:** ~1 hour on a single GPU.
+
+This was the **first test finetune run**, not a final production model. Training was done using **Unsloth** for speedup and Hugging Face TRL for supervised finetuning.
+
+---
+
+## Results
+
+- **Training Loss:** From **2.171600** to **0.9392** (at final step 843)
+- **Evaluation Loss:** From **2.198849** to **1.5074** (at final step 800)
+
+Training converged without issues. The loss metrics show expected early-stage improvement, but this checkpoint is **experimental** and requires further tuning and validation before use.
+
+---
+
+## Limitations
+
+- Experimental model — not yet optimized or fully Moroccan-Darija-aligned.
+- Performance outside Moroccan Arabic QA tasks may be limited.
+- Further finetuning and evaluation are needed before production use.
+
+## Uploaded finetuned model
+
+- **Developed by:** Lyte
+- **License:** apache-2.0
+- **Finetuned from model :** unsloth/gemma-3-1b-it-unsloth-bnb-4bit
+
+This gemma3_text model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.
+
+[<img src="https://raw.githubusercontent.com/unslothai/unsloth/main/images/unsloth%20made%20with%20love.png" width="200"/>](https://github.com/unslothai/unsloth)