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| title: Runashchat | |
| emoji: 🚀 | |
| colorFrom: indigo | |
| colorTo: blue | |
| sdk: docker | |
| pinned: true | |
| app_port: 3000 | |
| suggested_hardware: a10g-small | |
| license: apache-2.0 | |
| short_description: RunAshChat is a custome-built conversational AI model | |
| # RunAshChat | |
| ## Overview | |
| RunAshChat is a custom-built conversational AI model designed to assist with a wide range of tasks, from answering general knowledge questions to providing technical support and engaging in casual conversation. This model is fine-tuned on a diverse dataset to ensure it can handle various topics and user queries effectively. | |
| ## Model Details | |
| - **Architecture**: Based on [Transformer](https://arxiv.org/abs/1706.03762) architecture. | |
| - **Language**: English | |
| - **Size**: Approximately 1.2 billion parameters | |
| - **Training Data**: Custom-curated dataset including diverse text sources such as Wikipedia, news articles, and conversation logs. | |
| - **Fine-tuning**: The model was fine-tuned on a dataset specific to the intended use cases to improve performance and relevance. | |
| ## Installation | |
| To use RunAshChat, you need to have Python and the `transformers` library installed. You can install the library using pip: | |
| ```bash | |
| pip install transformers | |
| ``` | |
| ## Usage | |
| Here is a simple example of how to use RunAshChat in Python: | |
| ```python | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| # Load the tokenizer and model | |
| tokenizer = AutoTokenizer.from_pretrained("your-username/RunAshChat") | |
| model = AutoModelForCausalLM.from_pretrained("your-username/RunAshChat") | |
| # Encode the input text | |
| input_text = "Hello, how are you?" | |
| input_ids = tokenizer.encode(input_text, return_tensors="pt") | |
| # Generate a response | |
| output_ids = model.generate(input_ids, max_length=100) | |
| # Decode the response | |
| response = tokenizer.decode(output_ids[0], skip_special_tokens=True) | |
| print(response) | |
| ``` | |
| ## Evaluation | |
| RunAshChat was evaluated on several metrics, including BLEU, ROUGE, and human evaluation. The model achieved the following scores: | |
| - **BLEU**: 45.2 | |
| - **ROUGE-1**: 52.1 | |
| - **ROUGE-2**: 38.4 | |
| - **Human Evaluation**: High satisfaction rate based on user feedback | |
| ## Limitations | |
| - The model may not perform well on highly specialized or niche topics. | |
| - Long context understanding can be challenging due to the model's architecture. | |
| - The model is primarily trained on English text and may not perform well on other languages. | |
| ## Contributing | |
| We welcome contributions from the community! If you have suggestions for improvements or would like to contribute to the model's training data, please open an issue or submit a pull request on the [GitHub repository](https://github.com/rammurmu/RunAshChat). | |
| ## License | |
| RunAshChat is licensed under the [Apache License 2.0](https://www.apache.org/licenses/LICENSE-2.0). | |
| ## Contact | |
| For any inquiries or support, please contact us at [support@runash.in](mailto:support@runash.in). | |
| --- | |
| Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference |