Instructions to use mozilla-ai/WizardCoder-Python-34B-V1.0-llamafile with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mozilla-ai/WizardCoder-Python-34B-V1.0-llamafile with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mozilla-ai/WizardCoder-Python-34B-V1.0-llamafile", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download wizardcoder-python-34b-v1.0.Q4_K_S.llamafile from mozilla-ai/WizardCoder-Python-34B-V1.0-llamafile: direct link, hf CLI and curl.
- Browser
- Download file 19.2 GB
-
https://huggingface.co/mozilla-ai/WizardCoder-Python-34B-V1.0-llamafile/resolve/main/wizardcoder-python-34b-v1.0.Q4_K_S.llamafile
- Command line
-
hf download hf://mozilla-ai/WizardCoder-Python-34B-V1.0-llamafile/wizardcoder-python-34b-v1.0.Q4_K_S.llamafile
-
curl -L -o wizardcoder-python-34b-v1.0.Q4_K_S.llamafile https://huggingface.co/mozilla-ai/WizardCoder-Python-34B-V1.0-llamafile/resolve/main/wizardcoder-python-34b-v1.0.Q4_K_S.llamafile
19.2 GB
- Xet hash:
- 77971339f954f11fc41344ca361a36556426277284a0fe2d4e4e45fd8c07cb7a
- Size of remote file:
- 19.2 GB
- SHA256:
- c11b31e0ac2e42cae1bf75052ac4f57019c00d162d5430275dda40228fe42903
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.