Instructions to use dnnsdunca/Ddroidlabs-Codex-mini with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use dnnsdunca/Ddroidlabs-Codex-mini with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("<base-model-id>") model.load_adapter("dnnsdunca/Ddroidlabs-Codex-mini", set_active=True) - Notebooks
- Google Colab
- Kaggle
Download load-pretrained-model.py from dnnsdunca/Ddroidlabs-Codex-mini: direct link, hf CLI and curl.
- Browser
- Download file 301 Bytes
-
https://huggingface.co/dnnsdunca/Ddroidlabs-Codex-mini/resolve/main/load-pretrained-model.py
- Command line
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hf download hf://dnnsdunca/Ddroidlabs-Codex-mini/load-pretrained-model.py
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curl -L -o load-pretrained-model.py https://huggingface.co/dnnsdunca/Ddroidlabs-Codex-mini/resolve/main/load-pretrained-model.py
301 Bytes
| # load_pretrained_model.py | |
| from transformers import AutoModelForCausalLM, AutoTokenizer | |
| def load_model_and_tokenizer(): | |
| model_name = "gpt-3" | |
| tokenizer = AutoTokenizer.from_pretrained(model_name) | |
| model = AutoModelForCausalLM.from_pretrained(model_name) | |
| return model, tokenizer | |