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4iqq/phi-3-mini-instruct-128K-APPS-F16
phi-3-mini-instruct-128K-APPS-F16 is a text generation model from 4iqq. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as mit.
python from transformers import AutoModelForCausalLM, AutoTokenizer
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From the Hugging Face model README
# phi-3-mini-instruct-128K-APPS-F16
Fine-tuned Phi-3-mini-128K-instruct model specialized for reasoning and coding tasks.
## 🚀 Model Details
- **Base Model**: [microsoft/Phi-3-mini-128k-instruct](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct)
- **Adapter Used**: [AdnanRiaz107/CodePhi-3-mini-128k-instruct-APPS](https://huggingface.co/AdnanRiaz107/CodePhi-3-mini-128k-instruct-APPS)
- **Architecture**: Transformer-based language model
- **Context Length**: 128K tokens
- **Specialization**: Enhanced for complex reasoning and programming tasks
## 📊 Base Model Specifications
For complete technical specifications, hardware requirements, and performance characteristics, please refer to the official base model repository:
**[microsoft/Phi-3-mini-128k-instruct](https://huggingface.co/microsoft/Phi-3-mini-128k-instruct)**
## 🛠️ Training Approach
This model was created by applying the **CodePhi-3-mini-128k-instruct-APPS** adapter to the base Phi-3 model, further optimized for coding and reasoning tasks while maintaining the original 128K context window.
## 🔧 Usage
### Direct Inference
```python
from transformers import AutoModelForCausalLM, AutoTokenizer
model = AutoModelForCausalLM.from_pretrained(
"4iqq/phi-3-mini-instruct-128K-APPS-F16",
torch_dtype=torch.float16,
device_map="auto",
trust_remote_code=True
)
tokenizer = AutoTokenizer.from_pretrained(
"4iqq/phi-3-mini-instruct-128K-APPS-F16",
trust_remote_code=True
)
Convert to GGUF
python convert-hf-to-gguf.py 4iqq/phi-3-mini-instruct-128K-APPS-F16 --outtype f16
Further Fine-tuning
from peft import PeftModel, PeftConfig
model = PeftModel.from_pretrained(
"microsoft/Phi-3-mini-128k-instruct",
"4iqq/phi-3-mini-instruct-128K-APPS-F16"
)
📁 Repository Structure
This repository contains:
· Sharded model weights (model-0000x-of-0000x.safetensors) · Complete tokenizer files · Model configuration · Training adapters for further fine-tuning
🙏 Acknowledgments
· Microsoft for the base Phi-3-mini-128k-instruct model · AdnanRiaz107 for the original CodePhi-3 adapter
⚠️ Note
Model weights are provided in sharded format to support both:
· Direct GGUF conversion · Additional fine-tuning · Flexible deployment options
📄 License
Inherited from the base model - refer to microsoft/Phi-3-mini-128k-instruct for license details.