Instructions to use fagner/envoy with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fagner/envoy with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="fagner/envoy")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("fagner/envoy") model = AutoModelForTokenClassification.from_pretrained("fagner/envoy", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from fagner/envoy: direct link, hf CLI and curl.
- Browser
- Download file 3.06 kB
-
https://huggingface.co/fagner/envoy/resolve/main/training_args.bin
- Command line
-
hf download hf://fagner/envoy/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/fagner/envoy/resolve/main/training_args.bin
3.06 kB
- Xet hash:
- e69cfe4b01a5ab9e8af1cf92e958ddbad7319343e280e0b010ef903ad36a5373
- Size of remote file:
- 3.06 kB
- SHA256:
- 289790c3ee17f28436f1993d68436e419d5800ae5288688b3ce9ca02d7b8f557
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