Instructions to use YakovElm/test2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use YakovElm/test2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="YakovElm/test2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("YakovElm/test2") model = AutoModelForSequenceClassification.from_pretrained("YakovElm/test2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tf_model.h5 from YakovElm/test2: direct link, hf CLI and curl.
- Browser
- Download file 438 MB
-
https://huggingface.co/YakovElm/test2/resolve/main/tf_model.h5
- Command line
-
hf download hf://YakovElm/test2/tf_model.h5
-
curl -L -o tf_model.h5 https://huggingface.co/YakovElm/test2/resolve/main/tf_model.h5
438 MB
- Xet hash:
- 45fa11b49ec827eaebeaf72df5ecda8a1bbf1c4c44842a3f227003a0c04cc613
- Size of remote file:
- 438 MB
- SHA256:
- 74a524be4b01b44d2d8e75d576f4286eb6cc948d51be5886b8352e0ea3cc714a
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