Instructions to use SOTAagi2030/PocketIntent-Pilot with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SOTAagi2030/PocketIntent-Pilot with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SOTAagi2030/PocketIntent-Pilot")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("SOTAagi2030/PocketIntent-Pilot") model = AutoModelForSequenceClassification.from_pretrained("SOTAagi2030/PocketIntent-Pilot", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer/tokenizer.json from SOTAagi2030/PocketIntent-Pilot: direct link, hf CLI and curl.
- Browser
- Download file 174 Bytes
-
https://huggingface.co/SOTAagi2030/PocketIntent-Pilot/resolve/main/tokenizer/tokenizer.json
- Command line
-
hf download hf://SOTAagi2030/PocketIntent-Pilot/tokenizer/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/SOTAagi2030/PocketIntent-Pilot/resolve/main/tokenizer/tokenizer.json
174 Bytes
| {"version":"1.0","truncation":{"max_length":96},"model":{"type":"WordPiece","unk_token":"[UNK]","vocab":{"[UNK]":0,"billing":1,"network":2,"setup":3,"account":4,"pilot":5}}} | |