Instructions to use HUBioDataLab/freesolv_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HUBioDataLab/freesolv_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HUBioDataLab/freesolv_model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HUBioDataLab/freesolv_model") model = AutoModelForSequenceClassification.from_pretrained("HUBioDataLab/freesolv_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from HUBioDataLab/freesolv_model: direct link, hf CLI and curl.
- Browser
- Download file 2.93 kB
-
https://huggingface.co/HUBioDataLab/freesolv_model/resolve/98a45d1651522123bf296e94db4f3205e4f1ae18/training_args.bin
- Command line
-
hf download hf://HUBioDataLab/freesolv_model@98a45d1651522123bf296e94db4f3205e4f1ae18/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/HUBioDataLab/freesolv_model/resolve/98a45d1651522123bf296e94db4f3205e4f1ae18/training_args.bin
2.93 kB
- Xet hash:
- 7037c9ab4f497ddec45df7bfb7368e801300999ce0719e26becbfa999e22a723
- Size of remote file:
- 2.93 kB
- SHA256:
- 8e4f21eba4a12f4d4907a9ed935ae6f5c58aae9d1b52430bb1ad37f2bb8f99de
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.