Instructions to use tayyibsupercool/codellama_7b-resource_allocation-energy_efficiency_instruct_40k with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tayyibsupercool/codellama_7b-resource_allocation-energy_efficiency_instruct_40k with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("tayyibsupercool/codellama_7b-resource_allocation-energy_efficiency_instruct_40k", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Download tokenizer.json from tayyibsupercool/codellama_7b-resource_allocation-energy_efficiency_instruct_40k: direct link, hf CLI and curl.
- Browser
- Download file 1.84 MB
-
https://huggingface.co/tayyibsupercool/codellama_7b-resource_allocation-energy_efficiency_instruct_40k/resolve/main/tokenizer.json
- Command line
-
hf download hf://tayyibsupercool/codellama_7b-resource_allocation-energy_efficiency_instruct_40k/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/tayyibsupercool/codellama_7b-resource_allocation-energy_efficiency_instruct_40k/resolve/main/tokenizer.json
1.84 MB
File too large to display, you can check the raw version instead.