Neural Chat 7B v3
| Property | Value |
|---|---|
| Parameter Count | 7.24B |
| Base Model | Mistral-7B-v0.1 |
| License | Apache 2.0 |
| Training Hardware | Intel Gaudi 2 (8 cards) |
| Context Length | 8192 tokens |
| Paper | Research Paper |
What is neural-chat-7b-v3?
Neural Chat 7B v3 is Intel's advanced language model, fine-tuned from Mistral-7B using the SlimOrca dataset and optimized through Direct Preference Optimization (DPO). This model represents a significant improvement over its base model in several benchmark tests, particularly excelling in tasks like ARC and TruthfulQA.
Implementation Details
The model utilizes a sophisticated training approach with BF16 precision and supports multiple inference options, including FP32, BF16, and INT4 quantization. It was trained using the Adam optimizer with a cosine learning rate schedule and implements advanced features from the Mistral architecture.
- Supports multiple precision formats for flexible deployment
- Utilizes Intel's optimization frameworks for enhanced performance
- Implements efficient token handling with 8192 context length
- Features comprehensive fine-tuning capabilities
Core Capabilities
- Strong performance in benchmarks (67.15% on ARC, 83.29% on HellaSwag)
- Enhanced truthfulness with 58.77% on TruthfulQA
- Robust text generation and comprehension abilities
- Optimized for Intel hardware architecture
Frequently Asked Questions
Q: What makes this model unique?
The model combines Intel's hardware optimization with state-of-the-art language modeling capabilities, offering superior performance on truthfulness and reasoning tasks compared to its base model, while maintaining efficient resource utilization.
Q: What are the recommended use cases?
The model is well-suited for general language tasks, including text generation, comprehension, and analysis. It's particularly effective for applications requiring high accuracy in reasoning and truthful responses, though it should be fine-tuned for specific use cases.
