@@ -144,11 +144,11 @@ Use the provided scripts to export and optimize the models. When you run them, b
144144
145145Download the pre-optimized LLMs model
146146``` shell
147- huggingface-cli download OpenVINO/Qwen2.5-7B-Instruct-int4-ov --local-dir models/Qwen2.5-7B-Instruct-int4
147+ huggingface-cli download OpenVINO/Qwen2.5-7B-Instruct-int4-ov --local-dir models/Qwen2.5-7B-Instruct-INT4
148148```
149149Download the pre-optimized image generation model
150150``` shell
151- huggingface-cli download OpenVINO/FLUX.1-schnell-int4-ov --local-dir models/FLUX.1-schnell-int4
151+ huggingface-cli download OpenVINO/FLUX.1-schnell-int4-ov --local-dir models/FLUX.1-schnell-INT4
152152```
153153
154154## Convert and Optimize the Model (Option 2)
@@ -198,15 +198,15 @@ source venv/bin/activate # On Windows: venv\Scripts\activate
198198uvicorn main:app --host 0.0.0.0 --port 8000
199199
200200# Or run with custom model configuration. e.g., using the pre-optimized models above
201- IMAGE_MODEL_TYPE=" FLUX.1-schnell" LLM_MODEL_TYPE=" Qwen2.5-7B-Instruct" MODEL_PRECISION=" int4 " uvicorn main:app --host 0.0.0.0 --port 8000
201+ IMAGE_MODEL_TYPE=" FLUX.1-schnell" LLM_MODEL_TYPE=" Qwen2.5-7B-Instruct" MODEL_PRECISION=" INT4 " uvicorn main:app --host 0.0.0.0 --port 8000
202202```
203203
204204On Windows powershell:
205205
206206``` pwsh
207207$env:IMAGE_MODEL_TYPE="FLUX.1-schnell"
208208$env:LLM_MODEL_TYPE="Qwen2.5-7B-Instruct"
209- $env:MODEL_PRECISION="int4 "
209+ $env:MODEL_PRECISION="INT4 "
210210uvicorn main:app --host 0.0.0.0 --port 8000
211211```
212212
@@ -252,3 +252,4 @@ You can evaluate performance benchmarks for models like Qwen2.5-7B and FLUX.1-sc
252252<p align =" right " ><a href =" #top " >Back to top ⬆️</a ></p >
253253
254254<img referrerpolicy =" no-referrer-when-downgrade " src =" https://static.scarf.sh/a.png?x-pxid=7003a37c-568d-40a5-9718-0d021d8589ca?project=ai_ref_kits/multimodal_ai_visual_generator?file=README.md " />
255+
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