Instructions to use TomasJavurek/stepwise_eq_sft_model_multitask_test_resumed with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TomasJavurek/stepwise_eq_sft_model_multitask_test_resumed with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("TomasJavurek/stepwise_eq_sft_model_multitask_test_resumed", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from TomasJavurek/stepwise_eq_sft_model_multitask_test_resumed: direct link, hf CLI and curl.
- Browser
- Download file 20 MB
-
https://huggingface.co/TomasJavurek/stepwise_eq_sft_model_multitask_test_resumed/resolve/main/tokenizer.json
- Command line
-
hf download hf://TomasJavurek/stepwise_eq_sft_model_multitask_test_resumed/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/TomasJavurek/stepwise_eq_sft_model_multitask_test_resumed/resolve/main/tokenizer.json
20 MB
- Xet hash:
- df6faf08cf44dd0bb194a6fa846eddd17d20d2ec6eeb91296307dbc1c631dcd2
- Size of remote file:
- 20 MB
- SHA256:
- 7e7c4bce393169c6093143a0fa1f6cc9735ab7fafa5087367f7d0b0b9f15aa06
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