Instructions to use amartyasaran/LogLlama with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use amartyasaran/LogLlama with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/Llama-2-7b-chat-hf") model = PeftModel.from_pretrained(base_model, "amartyasaran/LogLlama") - Notebooks
- Google Colab
- Kaggle
Download emissions.csv from amartyasaran/LogLlama: direct link, hf CLI and curl.
- Browser
- Download file 808 Bytes
-
https://huggingface.co/amartyasaran/LogLlama/resolve/main/emissions.csv
- Command line
-
hf download hf://amartyasaran/LogLlama/emissions.csv
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curl -L -o emissions.csv https://huggingface.co/amartyasaran/LogLlama/resolve/main/emissions.csv
808 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 | |
| 2024-05-02T06:16:07,codecarbon,7bd21e85-5233-4abd-941c-9bfed0972068,29708.34127020836,3.6035622377806193,0.00012129799523322043,94.7671728360307,422.8977863787256,188.92139768600464,0.8239264042780955,3.306850877700807,1.5584769275080574,5.689254209486957,India,IND,uttar pradesh,,,Linux-4.15.0-122-generic-x86_64-with-glibc2.31,3.11.7,2.3.5,80,Intel(R) Xeon(R) CPU E5-2698 v4 @ 2.20GHz,3,3 x Tesla V100-SXM2-16GB,77.5358,28.4927,503.7903938293457,machine,N,1.0 | |