unsloth/Phi-4-mini-instruct-GGUF
NewMicrosoft Phi-4-mini distilled for edge reasoning. 3.8B params, 128K context, MIT license. Optimized for agentic tool-calling and multilingual tasks.
reasoningmultilingualtool-calling
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Microsoft Phi-4-mini distilled for step-by-step reasoning. 3.8B params, 128K context, MIT license. Unsloth bug-fixed GGUF for reliable agentic tool-calling.
How to Use
To get started, install the `transformers` library:
pip install transformersThen, use the following snippet to load the model:
from transformers import AutoTokenizer, AutoModelForCausalLM
model_id = "unsloth/Phi-4-mini-reasoning-GGUF"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)
# Your inference code here...Available Versions
Model Details
Teacher Model
Phi-4-14B-Reasoning
Distillation Method
Knowledge Distillation (Logits)
Training Dataset
Flickr30k (Conceptual)
Primary Task
Multimodal Generation
Performance Metrics (Example)
| Metric | Student Model | Teacher Model |
|---|---|---|
| Model Size | 2.49GB | 8.5GB |
| BLEU Score | 28.5 | 30.1 |