Instructions to use ksjpswaroop/Mixtral_Alpace_v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use ksjpswaroop/Mixtral_Alpace_v3 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("mistralai/Mixtral-8x7B-v0.1") model = PeftModel.from_pretrained(base_model, "ksjpswaroop/Mixtral_Alpace_v3") - Notebooks
- Google Colab
- Kaggle
Download emissions.csv from ksjpswaroop/Mixtral_Alpace_v3: direct link, hf CLI and curl.
- Browser
- Download file 772 Bytes
-
https://huggingface.co/ksjpswaroop/Mixtral_Alpace_v3/resolve/main/emissions.csv
- Command line
-
hf download hf://ksjpswaroop/Mixtral_Alpace_v3/emissions.csv
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curl -L -o emissions.csv https://huggingface.co/ksjpswaroop/Mixtral_Alpace_v3/resolve/main/emissions.csv
772 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 | |
| 2024-02-24T19:45:53,codecarbon,baaf397c-fd7b-493e-b522-f1b37aa2676b,16277.498822689056,2.9877217865122923,0.00018354919383239238,112.5,639.235,755.8777284622192,0.5086319814622404,3.9892933513158093,3.3733867182276898,7.871312051005719,United States,USA,,,,Linux-5.4.0-155-generic-x86_64-with-glibc2.31,3.9.7,2.2.3,256,AMD EPYC 7742 64-Core Processor,8,8 x NVIDIA A100-SXM4-80GB,-97.822,37.751,2015.673942565918,machine,N,1.0 | |