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README.md

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+Quantization made by Richard Erkhov.
+
+[Github](https://github.com/RichardErkhov)
+
+[Discord](https://discord.gg/pvy7H8DZMG)
+
+[Request more models](https://github.com/RichardErkhov/quant_request)
+
+
+OPT-1.3b-Chat - AWQ
+- Model creator: https://huggingface.co/KoalaAI/
+- Original model: https://huggingface.co/KoalaAI/OPT-1.3b-Chat/
+
+
+
+
+Original model description:
+---
+license: other
+widget:
+- text: 'What is the capital of France?'
+- text: 'What is wikipedia?'
+- text: 'What is a meme?'
+language:
+- en
+pipeline_tag: text-generation
+tags:
+- conversational
+- chat
+- assistant
+---
+# OPT-1.3b-Chat
+
+This is a text generation model based on the [OPT-1.3B](https://huggingface.co/facebook/opt-1.3b) model from Meta, trained using the Deepspeed library. The model can generate natural and engaging conversational responses given a user input.
+
+A Demo is [available here](https://huggingface.co/spaces/KoalaAI/OPT-Chat)
+The model is best at simple Q&A style questions, not open-ended ones like ChatGPT.
+
+## Training Details
+
+- The base model is [OPT-1.3B](https://huggingface.co/facebook/opt-1.3b), a decoder-only transformer with 1.3 billion parameters, pre-trained on a large text corpus using the causal language modeling objective.
+- The model was trained on a single NVIDIA A100 GPU using the Deepspeed pipeline parallelism and ZeRO optimizer.
+
+## Model Details
+- Number of parameters: 1.3 billion
+- Number of layers: 24
+- Number of attention heads: 16
+- Context size: 2048
+- Vocabulary size: 50,265
+- Embedding size: 1280
+- Feed-forward size: 5120
+- Dropout rate: 0.1
+
+## Usage
+
+You can use this model directly with the Hugging Face pipeline for text generation:
+
+```python
+from transformers import pipeline
+generator = pipeline('text-generation', model='DarwinAnim8or/OPT-1.3b-Chat')
+generator("Hello, how are you?")
+```
+
+### Suggested formatting
+The training data uses the following format:
+```
+Human: <question>
+Assistant: <answer>
+```
+
+It is recommended to follow the same format as closely as possible for the best results.
+We do intend on creating another model that is trained on the openassistant dataset in the future. 
+
+## License
+This model is licensed under the [OPT-175B license](https://github.com/facebookresearch/metaseq/blob/main/projects/OPT/MODEL_LICENSE.md), which is a non-commercial research license. Please read the full license terms before using this model.
+
+## Ethical Considerations
+This model is intended for research purposes only and should not be used for any malicious or harmful applications. The model may generate offensive or inappropriate content that does not reflect the views or opinions of the authors or Microsoft. Users are responsible for ensuring that the generated content complies with ethical and legal standards.
+