Update README.md

README.md

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----
-license: apache-2.0
----
+---
+license: apache-2.0
+datasets:
+- HuggingFaceFW/finewiki
+metrics:
+- accuracy
+base_model:
+- PaddlePaddle/PaddleOCR-VL
+new_version: zai-org/GLM-4.6
+pipeline_tag: translation
+library_name: adapter-transformers
+tags:
+- agent
+- code
+---
+# Trouter-20B
+
+## Model Description
+
+Trouter-20B is a 20 billion parameter language model designed for advanced natural language processing tasks.
+
+## Model Details
+
+- **Model Type:** Transformer-based Language Model
+- **Parameters:** 20 billion
+- **License:** Apache 2.0
+- **Language(s):** English (primary)
+- **Architecture:** Decoder-only transformer
+
+## Intended Uses
+
+### Direct Use
+
+This model can be used for:
+- Text generation
+- Question answering
+- Dialogue systems
+- Code completion
+- Creative writing assistance
+
+### Downstream Use
+
+Fine-tuning for specific tasks such as:
+- Domain-specific text generation
+- Instruction following
+- Specialized reasoning tasks
+
+### Out-of-Scope Use
+
+The model should not be used for:
+- Generating harmful, misleading, or illegal content
+- Making critical decisions without human oversight
+- Applications requiring perfect accuracy
+
+## Training Details
+
+### Training Data
+
+[Provide information about the training dataset, sources, and preprocessing]
+
+### Training Procedure
+
+[Describe the training methodology, hardware, and hyperparameters used]
+
+## Evaluation
+
+### Testing Data & Metrics
+
+[Include benchmark results and evaluation metrics]
+
+## Ethical Considerations
+
+Users should be aware of potential biases in the model and use appropriate safeguards in production environments.
+
+## How to Use
+
+```python
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+tokenizer = AutoTokenizer.from_pretrained("your-username/Trouter-20B")
+model = AutoModelForCausalLM.from_pretrained("your-username/Trouter-20B")
+
+inputs = tokenizer("Hello, how are you?", return_tensors="pt")
+outputs = model.generate(**inputs, max_length=50)
+print(tokenizer.decode(outputs[0]))
+```
+
+## Citation
+
+```bibtex
+@software{trouter20b,
+  title={Trouter-20B},
+  author={Your Name},
+  year={2025},
+  url={https://huggingface.co/your-username/Trouter-20B}
+}
+```
+
+## Contact
+
+For questions and feedback, please open an issue in the repository.