Instructions to use WinderBYZ/MyAwesomeModel-TestRepo-eta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use WinderBYZ/MyAwesomeModel-TestRepo-eta with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="WinderBYZ/MyAwesomeModel-TestRepo-eta")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("WinderBYZ/MyAwesomeModel-TestRepo-eta") model = AutoModel.from_pretrained("WinderBYZ/MyAwesomeModel-TestRepo-eta", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download eval_metrics.json from WinderBYZ/MyAwesomeModel-TestRepo-eta: direct link, hf CLI and curl.
- Browser
- Download file 69 Bytes
-
https://huggingface.co/WinderBYZ/MyAwesomeModel-TestRepo-eta/resolve/main/eval_metrics.json
- Command line
-
hf download hf://WinderBYZ/MyAwesomeModel-TestRepo-eta/eval_metrics.json
-
curl -L -o eval_metrics.json https://huggingface.co/WinderBYZ/MyAwesomeModel-TestRepo-eta/resolve/main/eval_metrics.json
69 Bytes
| { | |
| "eval_accuracy": 0.921, | |
| "latency_ms": 85, | |
| "memory_mb": 1905 | |
| } |