Model reference · open weights
react-native-executorch-clip-v-patch32 is an open-weight embedding model from software-mansion. AxForge deploys and operates it for you on dedicated EU-owned hardware — with the licence handled where one is required.
Available as managed deployment — configured and operated for you on dedicated EU hardware, quoted per deployment.
What it is
| Released by | software-mansion |
|---|---|
| Type | Embedding models |
| Task | Image embed |
| Runs with | executorch |
| Released | 2025-07-14 |
| Popularity | 9k downloads / month |
| Licence | Open weights |
About
This repository hosts the clip-vit-base-patch32 models exported for the
React Native ExecuTorch
library as ExecuTorch .pte programs, ready to run on device.
Upstream model: clip-vit-base-patch32
| Path | Component | Backend | Precision |
|---|---|---|---|
coreml/clip_vit_base_patch32_image_coreml_fp16.pte | image | coreml | fp16 |
coreml/clip_vit_base_patch32_text_coreml_fp16.pte | text | coreml | fp16 |
mlx/clip_vit_base_patch32_image_mlx_int8.pte | - | mlx | int8 |
vulkan/clip_vit_base_patch32_image_vulkan_fp16.pte | image | vulkan | fp16 |
vulkan/clip_vit_base_patch32_text_vulkan_fp16.pte | text | vulkan | fp16 |
xnnpack/clip_vit_base_patch32_image_xnnpack_fp32.pte | image | xnnpack | fp32 |
xnnpack/clip_vit_base_patch32_text_xnnpack_fp32.pte | text | xnnpack | fp32 |
config.json 43 B
coreml/clip_vit_base_patch32_image_coreml_fp16.pte 168 MB
coreml/clip_vit_base_patch32_text_coreml_fp16.pte 122 MB
coreml/config.json 1.7 kB
mlx/clip_vit_base_patch32_image_mlx_int8.pte 93.7 MB
mlx/config.json 840 B
tokenizer.json 2.1 MB
vulkan/clip_vit_base_patch32_image_vulkan_fp16.pte 168 MB
vulkan/clip_vit_base_patch32_text_vulkan_fp16.pte 121 MB
vulkan/config.json 1.7 kB
xnnpack/clip_vit_base_patch32_image_xnnpack_fp32.pte 335 MB
xnnpack/clip_vit_base_patch32_text_xnnpack_fp32.pte 242 MB
xnnpack/config.json 1.6 kB
These files are published for the ExecuTorch v1.4.1 runtime. ExecuTorch gives no forward compatibility guarantee, so an older runtime may fail to load them.
To use them in React Native ExecuTorch, pass the model constant shipped in the library's model registry to the corresponding task pipeline. See the documentation.
To load these files in your own ExecuTorch runtime, read the compatibility note first.
From the published model card. Full card on the HuggingFace links in the sidebar.
How it works
Using it via the API
Once AxForge deploys react-native-executorch-clip-v-patch32 for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (react-native-executorch-clip-v-patch32 below is illustrative; you get the exact model name on deployment.)
$ curl -sS https://api.axforge.ai/v1/embeddings \
-H "Authorization: Bearer $AXFORGE_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"react-native-executorch-clip-v-patch32","input":"text to embed"}'
Create an account — your API key is available in the console. 3M free tokens every 30 days with every new account.