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Phi2-GPTQ – AI Model by STiFLeR7 | AlphaNeural AI
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Phi2-GPTQ
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transformers
safetensors
phi
text-generation
gptq
quantized
causal-lm
pytorch
phi-2
microsoft/phi-2
quantized
apache-2.0
autotrain_compatible
text-generation-inference
endpoints_compatible
8-bit
us
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🧠 Phi-2 GPTQ (Quantized)
This repository provides a 4-bit GPTQ quantized version of the
Phi-2
model by Microsoft, optimized for efficient inference using
gptqmodel
.
📌 Model Details
Base Model
: Microsoft Phi-2
Quantization
: GPTQ (4-bit)
Quantizer
:
GPTQModel
Framework
: PyTorch + HuggingFace Transformers
Device Support
: CUDA (GPU)
License
: Apache 2.0
🚀 Features
✅ Lightweight: 4-bit quantization significantly reduces memory usage
✅ Fast Inference: Ideal for deployment on consumer GPUs
✅ Compatible: Works with
transformers
,
optimum
, and
gptqmodel
✅ CUDA-accelerated: Automatically uses GPU for speed
📚 Usage
This model is ready-to-use with the Hugging Face
transformers
library.
🧪 Intended Use
Research and development
Prototyping generative applications
Fast inference environments with limited GPU memory
📖 References
Microsoft Phi-2:
https://huggingface.co/microsoft/phi-2
GPTQModel:
https://github.com/ModelCoud/GPTQModel
Transformers:
https://github.com/huggingface/transformers
⚖️ License
This model is distributed under the
Apache License 2.0
.
