Instructions to use bgsach/WizardCoder-Python-7B-V1.0-ct2-int8_float16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use bgsach/WizardCoder-Python-7B-V1.0-ct2-int8_float16 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("bgsach/WizardCoder-Python-7B-V1.0-ct2-int8_float16", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download model.bin from bgsach/WizardCoder-Python-7B-V1.0-ct2-int8_float16: direct link, hf CLI and curl.
- Browser
- Download file 6.74 GB
-
https://huggingface.co/bgsach/WizardCoder-Python-7B-V1.0-ct2-int8_float16/resolve/main/model.bin
- Command line
-
hf download hf://bgsach/WizardCoder-Python-7B-V1.0-ct2-int8_float16/model.bin
-
curl -L -o model.bin https://huggingface.co/bgsach/WizardCoder-Python-7B-V1.0-ct2-int8_float16/resolve/main/model.bin
6.74 GB
- Xet hash:
- d685974b86244d693f99739dc7d114338ba7f4ddc778747db1a26c3812fc53c8
- Size of remote file:
- 6.74 GB
- SHA256:
- 14b0bfbd0586dfafd5ba579e2cf386bbb419c2308f30e8ba1be8e41047d6b9fd
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