Instructions to use chasedreaminf/intent_cls_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chasedreaminf/intent_cls_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="chasedreaminf/intent_cls_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("chasedreaminf/intent_cls_model") model = AutoModelForSequenceClassification.from_pretrained("chasedreaminf/intent_cls_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from chasedreaminf/intent_cls_model: direct link, hf CLI and curl.
- Browser
- Download file 4.66 kB
-
https://huggingface.co/chasedreaminf/intent_cls_model/resolve/main/training_args.bin
- Command line
-
hf download hf://chasedreaminf/intent_cls_model/training_args.bin
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curl -L -o training_args.bin https://huggingface.co/chasedreaminf/intent_cls_model/resolve/main/training_args.bin
4.66 kB
- Xet hash:
- dcd1ed6c26c2b89b6b64c708864ca56faca434d8553b2d629b9cfcc5d626b4b6
- Size of remote file:
- 4.66 kB
- SHA256:
- 41b50540e2fc3b1c906f586ee982c2ebe0ce0160135fa72c7a81ad1454c03d7b
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