Instructions to use NLP-Search/final-model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NLP-Search/final-model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NLP-Search/final-model")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NLP-Search/final-model") model = AutoModelForMaskedLM.from_pretrained("NLP-Search/final-model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from NLP-Search/final-model: direct link, hf CLI and curl.
- Browser
- Download file 2.8 kB
-
https://huggingface.co/NLP-Search/final-model/resolve/main/training_args.bin
- Command line
-
hf download hf://NLP-Search/final-model/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/NLP-Search/final-model/resolve/main/training_args.bin
2.8 kB
- Xet hash:
- 4ae9a42155ab84502d75c1f2c39eebb2d591fab9764ac5091f86304a6722228d
- Size of remote file:
- 2.8 kB
- SHA256:
- 6e800d57b22bc06013271b79b9ef3469721c433bc999460071096e134fab84ce
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