Text Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use dzinampini/api_endpoint_extractor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dzinampini/api_endpoint_extractor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="dzinampini/api_endpoint_extractor")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("dzinampini/api_endpoint_extractor") model = AutoModelForSequenceClassification.from_pretrained("dzinampini/api_endpoint_extractor", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from dzinampini/api_endpoint_extractor: direct link, hf CLI and curl.
- Browser
- Download file 5.3 kB
-
https://huggingface.co/dzinampini/api_endpoint_extractor/resolve/main/training_args.bin
- Command line
-
hf download hf://dzinampini/api_endpoint_extractor/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/dzinampini/api_endpoint_extractor/resolve/main/training_args.bin
5.3 kB
- Xet hash:
- b7b80777e07bb7f6e12edcbe9bff59f9d64448ce6b8c45dc366f85ba5eaabce7
- Size of remote file:
- 5.3 kB
- SHA256:
- 9c4d5da37b101d6a43b2c2e3e827669f544e36fab523f412bc0d0db38a2bc970
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