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README.md

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 ---
+pipeline_tag: text-generation
+library_name: transformers
+language:
+  - en
 license: fair-noncommercial-research-license
+datasets:
+  - malte0621/test-dataset
 ---
+# Test Model
+This is a model created for testing purposes. It is one of the smallest models available on Hugging Face, designed to experiment with the capabilities of small/tiny models.
+
+## Model Structure
+The model is structured to handle text generation tasks. It is trained on a small dataset that consists of user prompts and AI responses, allowing it to generate text based on given inputs.
+
+## Usage
+You can use this model for text generation tasks, particularly for testing and experimentation with small models. It is not intended for production use or serious applications.
+
+### Prompt format
+```
+<|user|>Your input prompt here<|ai|>The model's response will be generated here<|stop|>
+```
+
+### Example Usage
+
+
+#### Transformers
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
+model_name = "Malte0621/test-model"
+model = AutoModelForCausalLM.from_pretrained(model_name, gguf_file="model.gguf")
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+prompt = "<|user|>Hi there!<|ai|>"
+response = model.generate(tokenizer(prompt, return_tensors="pt").input_ids)
+print(tokenizer.decode(response[0], skip_special_tokens=True))
+```
+
+#### llama.cpp
+```bash
+./llama-cli -m model.gguf -p "<|user|>Hi there!<|ai|>" -n 128 -no-cnv --rope-freq-scale 0.125
+```
+
+#### LM Studio
+https://model.lmstudio.ai/download/Malte0621/test
+**(Make sure to set the RoPE frequency scale to 0.125 in the model settings.)**
+
+## License
+This model is released under the [Fair Noncommercial Research License](https://huggingface.co/Malte0621/test/blob/main/LICENSE).
+
+## Citation
+If you use this model in your research, please cite it as follows:
+```
+@misc{test-model,
+  author = {Malte0621},
+  title = {Test-Model},
+  year = {2025},
+  url = {https://huggingface.co/Malte0621/test}
+}
+```
+
+## Acknowledgements
+This model was created as part of a personal project to explore the capabilities of small language models. It is not affiliated with any organization or commercial entity.

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