Instructions to use TomasJavurek/stepwise_eq_sft_model_multitask_v2 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_v2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("TomasJavurek/stepwise_eq_sft_model_multitask_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from TomasJavurek/stepwise_eq_sft_model_multitask_v2: direct link, hf CLI and curl.
- Browser
- Download file 20 MB
-
https://huggingface.co/TomasJavurek/stepwise_eq_sft_model_multitask_v2/resolve/main/tokenizer.json
- Command line
-
hf download hf://TomasJavurek/stepwise_eq_sft_model_multitask_v2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/TomasJavurek/stepwise_eq_sft_model_multitask_v2/resolve/main/tokenizer.json
20 MB
- Xet hash:
- 3af83c8a9f9fde39cba0757b7bf23826e05e7e731da153d131e0d56ad6a7d1f3
- Size of remote file:
- 20 MB
- SHA256:
- e5312e432f5984f829c6bb4ec3a3219864f761263c1e8a2e87f105b328dc6691
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