Instructions to use txt2audio/custom-mymodel_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use txt2audio/custom-mymodel_v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="txt2audio/custom-mymodel_v1", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("txt2audio/custom-mymodel_v1", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from txt2audio/custom-mymodel_v1: direct link, hf CLI and curl.
- Browser
- Download file 7.05 kB
-
https://huggingface.co/txt2audio/custom-mymodel_v1/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://txt2audio/custom-mymodel_v1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/txt2audio/custom-mymodel_v1/resolve/main/pytorch_model.bin
7.05 kB
- Xet hash:
- ad8d0781d7136586010ca1fe778a3d612f60409df581e942aba29144034da555
- Size of remote file:
- 7.05 kB
- SHA256:
- d3aaeadc87c87d041089e8ab0de07af2779cd0ff5952b2ecb477aa4301484f1f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.