Mistral-7B-Instruct-v0.2-code-ft
I'm thrilled to introduce the latest iteration of our model, Mistral-7B-Instruct-v0.2-code-ft. This updated version is designed to further enhance coding assistance and co-pilot functionalities. We're eager for developers and enthusiasts to try it out and provide feedback!
Additional Information
This version builds upon the previous Mistral-7B models, incorporating new datasets and features for a more refined experience.
Prompt template: ChatML
<|im_start|>system
{system_message}<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant
Quantised Model Links:
- https://huggingface.co./LoneStriker/Mistral-7B-Instruct-v0.2-code-ft-8.0bpw-h8-exl2
- https://huggingface.co./TheBloke/Mistral-7B-Instruct-v0.2-code-ft-GGUF
- https://huggingface.co./TheBloke/Mistral-7B-Instruct-v0.2-code-ft-AWQ
- https://huggingface.co./TheBloke/Mistral-7B-Instruct-v0.2-code-ft-GPTQ
Eval Plus Performance
For detailed performance metrics, visit Eval Plus page: Mistral-7B-Instruct-v0.2-code-ft Eval Plus
Score: 0.421
Dataset:
The model has been trained on a new dataset to improve its performance and versatility:
path: ajibawa-2023/Code-74k-ShareGPT
type: sharegpt
conversation: chatml
Find more about the dataset here: Code-74k-ShareGPT Dataset
Model Architecture
- Base Model: mistralai/Mistral-7B-Instruct-v0.2
- Tokenizer Type: LlamaTokenizer
- Model Type: MistralForCausalLM
- Is Mistral Derived Model: true
- Sequence Length: 16384 with sample packing
Enhanced Features
- Adapter: qlora
- Learning Rate: 0.0002 with cosine lr scheduler
- Optimizer: adamw_bnb_8bit
- Training Enhancements: bf16 training, gradient checkpointing, and flash attention
Download Information
You can download and explore this model through these links on Hugging Face.
Contributions and Feedback
We welcome contributions and feedback from the community. Please feel free to open issues or pull requests on repository.
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