Text Classification
Transformers
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use nlpllm007/results_classification with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nlpllm007/results_classification with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="nlpllm007/results_classification")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("nlpllm007/results_classification") model = AutoModelForSequenceClassification.from_pretrained("nlpllm007/results_classification", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from nlpllm007/results_classification: direct link, hf CLI and curl.
- Browser
- Download file 5.05 kB
-
https://huggingface.co/nlpllm007/results_classification/resolve/main/training_args.bin
- Command line
-
hf download hf://nlpllm007/results_classification/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/nlpllm007/results_classification/resolve/main/training_args.bin
5.05 kB
- Xet hash:
- c2a980a7889cddfed0d99a0b7f288eff077e37e30236a62a4f10682670bf1065
- Size of remote file:
- 5.05 kB
- SHA256:
- 2a7a77e7c8fc3cd455bb2259c25c4b352c6d83598031c48d8f3dfd5bd9113cf0
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