Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use ASCCCCCCCC/distilbert-base-uncased-finetuned-clinc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ASCCCCCCCC/distilbert-base-uncased-finetuned-clinc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ASCCCCCCCC/distilbert-base-uncased-finetuned-clinc")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ASCCCCCCCC/distilbert-base-uncased-finetuned-clinc") model = AutoModelForSequenceClassification.from_pretrained("ASCCCCCCCC/distilbert-base-uncased-finetuned-clinc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from ASCCCCCCCC/distilbert-base-uncased-finetuned-clinc: direct link, hf CLI and curl.
- Browser
- Download file 268 MB
-
https://huggingface.co/ASCCCCCCCC/distilbert-base-uncased-finetuned-clinc/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://ASCCCCCCCC/distilbert-base-uncased-finetuned-clinc/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/ASCCCCCCCC/distilbert-base-uncased-finetuned-clinc/resolve/main/pytorch_model.bin
268 MB
- Xet hash:
- 8267464d7755f2bcbec1431812d22f3001023602cb97a02aca2ee23aaf1c412f
- Size of remote file:
- 268 MB
- SHA256:
- 3b664afc7f4bcb959cca7f508936095f79ce0111904f0178d282bbdaf972e6f6
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