Instructions to use Ameer05/test with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Ameer05/test with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "summarization" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("summarization", model="Ameer05/test")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Ameer05/test") model = AutoModelForSeq2SeqLM.from_pretrained("Ameer05/test", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from Ameer05/test: direct link, hf CLI and curl.
- Browser
- Download file 3.06 kB
-
https://huggingface.co/Ameer05/test/resolve/main/training_args.bin
- Command line
-
hf download hf://Ameer05/test/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/Ameer05/test/resolve/main/training_args.bin
3.06 kB
- Xet hash:
- 95ff75ed1f7940f0b4d128d5ddd777a74aac9cc40c95cd24a10f5cde60267ede
- Size of remote file:
- 3.06 kB
- SHA256:
- ccd8abfadafcc22f3a9f77f7eb0b7aa841ac2ef2a18675a16504d553574a276c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.