Instructions to use tarekziade/results with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tarekziade/results with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="tarekziade/results")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("tarekziade/results") model = AutoModelForSequenceClassification.from_pretrained("tarekziade/results", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download codecarbon.csv from tarekziade/results: direct link, hf CLI and curl.
- Browser
- Download file 736 Bytes
-
https://huggingface.co/tarekziade/results/resolve/main/codecarbon.csv
- Command line
-
hf download hf://tarekziade/results/codecarbon.csv
-
curl -L -o codecarbon.csv https://huggingface.co/tarekziade/results/resolve/main/codecarbon.csv
736 Bytes
| timestamp,project_name,run_id,duration,emissions,emissions_rate,cpu_power,gpu_power,ram_power,cpu_energy,gpu_energy,ram_energy,energy_consumed,country_name,country_iso_code,region,cloud_provider,cloud_region,os,python_version,codecarbon_version,cpu_count,cpu_model,gpu_count,gpu_model,longitude,latitude,ram_total_size,tracking_mode,on_cloud,pue | |
| 2024-05-07T13:54:33,codecarbon,9b2a43db-5992-46d8-ac23-3edc602667fc,16803.414182901382,0.007290563515903978,4.3387393993552947e-07,1.7961000000000003,0.0061,12.0,0.008076271469301885,0.06700463383336423,0.0331037439910571,0.10818464929372278,France,FRA,provence-alpes-côte d'azur,,,macOS-14.4.1-arm64-arm-64bit,3.11.4,2.3.4,10,Apple M1 Pro,1,Apple M1 Pro,5.4125,43.3178,32.0,machine,N,1.0 | |