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 tokenizer_config.json from dzinampini/api_endpoint_extractor: direct link, hf CLI and curl.
- Browser
- Download file 48 Bytes
-
https://huggingface.co/dzinampini/api_endpoint_extractor/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://dzinampini/api_endpoint_extractor/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/dzinampini/api_endpoint_extractor/resolve/main/tokenizer_config.json
48 Bytes
| {"do_lower_case": true, "model_max_length": 512} |