AngelRaychev/0.5B-policy-iteration_1
AngelRaychev/0.5B-policy-iteration_1 is a 0.5 billion parameter language model fine-tuned from AngelRaychev/0.5B-policy-iteration_0 using the TRL framework. This model is trained with Supervised Fine-Tuning (SFT) and is designed for text generation tasks. It is suitable for applications requiring a compact model for generating conversational responses.
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Model Overview
AngelRaychev/0.5B-policy-iteration_1 is a 0.5 billion parameter language model developed by AngelRaychev. It is a fine-tuned iteration of the AngelRaychev/0.5B-policy-iteration_0 base model, specifically trained using the TRL (Transformer Reinforcement Learning) framework.
Key Capabilities
- Text Generation: The model is primarily designed for generating human-like text based on given prompts.
- Instruction Following: Trained with Supervised Fine-Tuning (SFT), it can generate responses to specific questions or instructions, as demonstrated by the quick start example.
Training Details
This model was trained using Supervised Fine-Tuning (SFT) within the TRL framework. The training utilized specific versions of key libraries:
- TRL: 0.16.1
- Transformers: 4.51.2
- Pytorch: 2.6.0
- Datasets: 3.5.0
- Tokenizers: 0.21.1
Good For
- Conversational AI: Generating responses in interactive applications.
- Prototyping: Quickly setting up text generation capabilities with a smaller model.
- Further Fine-tuning: Serving as a base for additional domain-specific fine-tuning due to its SFT training.