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 README.md from YakovElm/test2: direct link, hf CLI and curl.
- Browser
- Download file 930 Bytes
-
https://huggingface.co/YakovElm/test2/resolve/main/README.md
- Command line
-
hf download hf://YakovElm/test2/README.md
-
curl -L -o README.md https://huggingface.co/YakovElm/test2/resolve/main/README.md
930 Bytes
| license: apache-2.0 | |
| tags: | |
| - generated_from_keras_callback | |
| model-index: | |
| - name: test2 | |
| results: [] | |
| <!-- This model card has been generated automatically according to the information Keras had access to. You should | |
| probably proofread and complete it, then remove this comment. --> | |
| # test2 | |
| This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset. | |
| It achieves the following results on the evaluation set: | |
| ## Model description | |
| More information needed | |
| ## Intended uses & limitations | |
| More information needed | |
| ## Training and evaluation data | |
| More information needed | |
| ## Training procedure | |
| ### Training hyperparameters | |
| The following hyperparameters were used during training: | |
| - optimizer: None | |
| - training_precision: float32 | |
| ### Training results | |
| ### Framework versions | |
| - Transformers 4.29.2 | |
| - TensorFlow 2.12.0 | |
| - Datasets 2.12.0 | |
| - Tokenizers 0.13.3 | |