OpenAssistant-Pythia-12B

Open-Assistant SFT-4 12B Model is an English language AI assistant developed through supervised fine-tuning of a large language model. This tool is designed to engage in human-like conversations and provide assistance across a wide range of topics.

Key features:
- Conversational AI: Capable of engaging in natural language interactions on various subjects
- Multilingual Support: Trained on data from multiple languages, enhancing its ability to understand and respond in different linguistic contexts
- Fine-tuned Performance: Based on the Pythia 12B model, further refined with human-generated conversational data
- Open-source Development: Created through collaborative efforts of Open-Assistant contributors

How it works:
1. User inputs a prompt or question using the <|prompter|> token
2. The input is processed by the model
3. The model generates a response, marked by the <|assistant|> token
4. The conversation continues with alternating user and assistant turns, each ending with <|endoftext|> token

Use of AI:
The model utilizes transformer-based architecture to process and generate human-like text. It has been trained on a diverse dataset of conversations to improve its ability to understand context and provide relevant responses.

AI foundation model:
The Open-Assistant SFT-4 12B Model is built upon the EleutherAI Pythia 12B model, which has been further fine-tuned using supervised learning techniques on human-generated conversational data.

Target users:
- Developers integrating conversational AI into applications
- Researchers studying natural language processing and AI assistants
- Individuals or organizations seeking an open-source alternative to proprietary AI assistants

How to access:
The model is available under the Apache 2.0 license. Users can access the code through the Open-Assistant GitHub repository and join the Open-Assistant Discord for community support and discussions.

Technical specifications:
- Model Type: Transformer-based Language Model
- Base Model: EleutherAI / pythia-12b-deduped
- Training Data: Conversations collected through open-assistant.io before March 25, 2023
- Checkpoint: 4000 steps
- Maximum Input Length: 2048 tokens

Development details:
- Training Command: Utilizes DeepSpeed for distributed training
- Learning Rate: 6e-6
- Weight Decay: 0.0
- Gradient Accumulation Steps: 2
- Per Device Train Batch Size: 4
- Training Epochs: 8