Instructions to use tachiwin/language_classification_curricular_checkpoints with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tachiwin/language_classification_curricular_checkpoints with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="tachiwin/language_classification_curricular_checkpoints")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("tachiwin/language_classification_curricular_checkpoints") model = AutoModelForSpeechSeq2Seq.from_pretrained("tachiwin/language_classification_curricular_checkpoints", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download last-checkpoint/optimizer.pt from tachiwin/language_classification_curricular_checkpoints: direct link, hf CLI and curl.
- Browser
- Download file 2.06 GB
-
https://huggingface.co/tachiwin/language_classification_curricular_checkpoints/resolve/main/last-checkpoint/optimizer.pt
- Command line
-
hf download hf://tachiwin/language_classification_curricular_checkpoints/last-checkpoint/optimizer.pt
-
curl -L -o optimizer.pt https://huggingface.co/tachiwin/language_classification_curricular_checkpoints/resolve/main/last-checkpoint/optimizer.pt
2.06 GB
- Xet hash:
- 6d53c2e4edc5f7ed2d1da075498f4505455cd71902744deffb7d5f84fbe23662
- Size of remote file:
- 2.06 GB
- SHA256:
- bca2f83c7c62bb2baeb05f97ac5a95135b02a1d4757160680bb94bbe4a6a7b0a
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