Instructions to use amd/Phi-3.5-mini-instruct-onnx-ryzenai-npu with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use amd/Phi-3.5-mini-instruct-onnx-ryzenai-npu with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="amd/Phi-3.5-mini-instruct-onnx-ryzenai-npu")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("amd/Phi-3.5-mini-instruct-onnx-ryzenai-npu", device_map="auto")

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use amd/Phi-3.5-mini-instruct-onnx-ryzenai-npu with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "amd/Phi-3.5-mini-instruct-onnx-ryzenai-npu"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "amd/Phi-3.5-mini-instruct-onnx-ryzenai-npu",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/amd/Phi-3.5-mini-instruct-onnx-ryzenai-npu

SGLang

How to use amd/Phi-3.5-mini-instruct-onnx-ryzenai-npu with SGLang:

Install from pip and serve model

# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
    --model-path "amd/Phi-3.5-mini-instruct-onnx-ryzenai-npu" \
    --host 0.0.0.0 \
    --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "amd/Phi-3.5-mini-instruct-onnx-ryzenai-npu",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker images

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:latest \
    python3 -m sglang.launch_server \
        --model-path "amd/Phi-3.5-mini-instruct-onnx-ryzenai-npu" \
        --host 0.0.0.0 \
        --port 30000
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:30000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "amd/Phi-3.5-mini-instruct-onnx-ryzenai-npu",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use amd/Phi-3.5-mini-instruct-onnx-ryzenai-npu with Docker Model Runner:
```
docker model run hf.co/amd/Phi-3.5-mini-instruct-onnx-ryzenai-npu
```

Lemonade

How to use amd/Phi-3.5-mini-instruct-onnx-ryzenai-npu with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull amd/Phi-3.5-mini-instruct-onnx-ryzenai-npu

Run and chat with the model (requires XDNA 2 NPU)

lemonade run user.Phi-3.5-mini-instruct-onnx-ryzenai-npu

List all available models

lemonade list

sshukla4 commited on Oct 2, 2025

Commit

6e362d5

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Update README.md

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@@ -1,40 +1,47 @@
 ---
 language:
-- zh
-- en
 tags:
-- glm
-- chatglm
-- thudm
 - ryzenai-npu
-base_model: THUDM/chatglm3-6b
 ---
-# chatglm3-6b
 - ## Introduction
   This model was created using Quark Quantization, followed by OGA Model Builder, and finalized with post-processing for NPU deployment.
 - ## Quantization Strategy
-  - AWQ / Group 128 / Asymmetric / BF16 activations / UINT4 weights
 - ## Quick Start
-For quickstart, refer to [Ryzen AI doucmentation](https://ryzenai.docs.amd.com/en/latest/npu_oga.html)
-#### Evaluation scores
-The perplexity measurement is run on the wikitext-2-raw-v1 (raw data) dataset provided by Hugging Face. Perplexity score measured for prompt length 2k is 29.81679.
 #### License
 Modifications copyright(c) 2024 Advanced Micro Devices,Inc. All rights reserved.
-Licensed under the Apache License, Version 2.0 (the "License");
-you may not use this file except in compliance with the License.
-You may obtain a copy of the License at
-    http://www.apache.org/licenses/LICENSE-2.0
-Unless required by applicable law or agreed to in writing, software
-distributed under the License is distributed on an "AS IS" BASIS,
-WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-See the License for the specific language governing permissions and
-limitations under the License.

 ---
+license: mit
 language:
+- multilingual
+base_model:
+- microsoft/Phi-3.5-mini-instruct
+pipeline_tag: text-generation
+library_name: transformers
 tags:
+- nlp
+- code
+- onnx
+- amd
 - ryzenai-npu
 ---
+# Phi-3.5-mini-instruct-onnx-ryzenai-npu
 - ## Introduction
   This model was created using Quark Quantization, followed by OGA Model Builder, and finalized with post-processing for NPU deployment.
 - ## Quantization Strategy
+  - AWQ / Group 128 / Asymmetric / BFP16 activations / UINT4 Weights
 - ## Quick Start
+  For quickstart, refer to [Ryzen AI documentation](https://ryzenai.docs.amd.com/en/latest/npu_oga.html)
+## Evaluation scores
+  - The perplexity measurement is run on the wikitext-2-raw-v1 (raw data) dataset provided by Hugging Face. Perplexity score measured for prompt length 2k is 6.8701.
+  - The average MMLU scores are astronomy - 75, philosophy - 69.77 and management - 79.61.
 #### License
 Modifications copyright(c) 2024 Advanced Micro Devices,Inc. All rights reserved.
+MIT License
+Copyright (c) 2024 Advanced Micro Devices, Inc
+Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
+The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+license: MIT license