Instructions to use ashesicsis1/lv60-languageModel with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ashesicsis1/lv60-languageModel with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="ashesicsis1/lv60-languageModel")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForCTC processor = AutoProcessor.from_pretrained("ashesicsis1/lv60-languageModel") model = AutoModelForCTC.from_pretrained("ashesicsis1/lv60-languageModel", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ashesicsis1/lv60-languageModel: direct link, hf CLI and curl.
- Browser
- Download file 1.26 GB
-
https://huggingface.co/ashesicsis1/lv60-languageModel/resolve/refs%2Fpr%2F1/pytorch_model.bin
- Command line
-
hf download hf://ashesicsis1/lv60-languageModel@refs/pr/1/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ashesicsis1/lv60-languageModel/resolve/refs%2Fpr%2F1/pytorch_model.bin
1.26 GB
- Xet hash:
- 78251a6cef2cb7d4ecf55a2fd5287dba074046bc8e7fa7b14e60a67ecad9e246
- Size of remote file:
- 1.26 GB
- SHA256:
- 704e834643c6ed4903237e1d616e19f2454f8284126308fdcbf3e39c7ee77a4f
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