Instructions to use YakovElm/Apache_5_GPT2_Microsoft_Normal with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YakovElm/Apache_5_GPT2_Microsoft_Normal with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YakovElm/Apache_5_GPT2_Microsoft_Normal")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YakovElm/Apache_5_GPT2_Microsoft_Normal") model = AutoModelForSequenceClassification.from_pretrained("YakovElm/Apache_5_GPT2_Microsoft_Normal", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download pytorch_model.bin from YakovElm/Apache_5_GPT2_Microsoft_Normal: direct link, hf CLI and curl.
- Browser
- Download file 1.44 GB
-
https://huggingface.co/YakovElm/Apache_5_GPT2_Microsoft_Normal/resolve/main/pytorch_model.bin
- Command line
-
hf download hf://YakovElm/Apache_5_GPT2_Microsoft_Normal/pytorch_model.bin
-
curl -L -o pytorch_model.bin https://huggingface.co/YakovElm/Apache_5_GPT2_Microsoft_Normal/resolve/main/pytorch_model.bin
1.44 GB
- Xet hash:
- 4d840d5b467a28fa965dff9d7def6abe496b557ef5e788a89e2e41e6db14dcda
- Size of remote file:
- 1.44 GB
- SHA256:
- 4eed81ac7b9f52b7059321d6c18cdd20464979d52a9b51ecd754a0dd21182420
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