Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use metamath/distilbert-base-uncased-finetuned-clinc with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use metamath/distilbert-base-uncased-finetuned-clinc with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="metamath/distilbert-base-uncased-finetuned-clinc")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("metamath/distilbert-base-uncased-finetuned-clinc") model = AutoModelForSequenceClassification.from_pretrained("metamath/distilbert-base-uncased-finetuned-clinc", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download run-11/checkpoint-1500/training_args.bin from metamath/distilbert-base-uncased-finetuned-clinc: direct link, hf CLI and curl.
- Browser
- Download file 4.73 kB
-
https://huggingface.co/metamath/distilbert-base-uncased-finetuned-clinc/resolve/main/run-11/checkpoint-1500/training_args.bin
- Command line
-
hf download hf://metamath/distilbert-base-uncased-finetuned-clinc/run-11/checkpoint-1500/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/metamath/distilbert-base-uncased-finetuned-clinc/resolve/main/run-11/checkpoint-1500/training_args.bin
4.73 kB
- Xet hash:
- ffc95b39472089e12feae473693a464b4c180b40f46572ad44ced5d6c7b8b394
- Size of remote file:
- 4.73 kB
- SHA256:
- 68e460dde601081e84554087a0250ba9bc087807fc65e5589aa1d668d70a78c3
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