Token Classification
Transformers
PyTorch
TensorBoard
French
flaubert
bert
natural language understanding
NLU
spoken language understanding
SLU
understanding
MEDIA
Instructions to use vpelloin/MEDIA_NLU-flaubert_oral_asr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vpelloin/MEDIA_NLU-flaubert_oral_asr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="vpelloin/MEDIA_NLU-flaubert_oral_asr")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("vpelloin/MEDIA_NLU-flaubert_oral_asr") model = AutoModelForTokenClassification.from_pretrained("vpelloin/MEDIA_NLU-flaubert_oral_asr", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 88328d8f0e05d3fa1729c763468a96b73a230186eaaa41299947f5ed8007677e
- Size of remote file:
- 550 MB
- SHA256:
- 5f450bc733f5bd114cd03af88025f9e45607824ee559c5c033fdbfd51096f388
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