Instructions to use zpdeaccount/old-bart-finetuned-pressrelease with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zpdeaccount/old-bart-finetuned-pressrelease 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="zpdeaccount/old-bart-finetuned-pressrelease")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("zpdeaccount/old-bart-finetuned-pressrelease") model = AutoModelForSeq2SeqLM.from_pretrained("zpdeaccount/old-bart-finetuned-pressrelease", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from zpdeaccount/old-bart-finetuned-pressrelease: direct link, hf CLI and curl.
- Browser
- Download file 3.32 kB
-
https://huggingface.co/zpdeaccount/old-bart-finetuned-pressrelease/resolve/main/training_args.bin
- Command line
-
hf download hf://zpdeaccount/old-bart-finetuned-pressrelease/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/zpdeaccount/old-bart-finetuned-pressrelease/resolve/main/training_args.bin
3.32 kB
- Xet hash:
- 47dd2adb1a8f2a0bc0c4d8986494aca83f697bfe5587b173de7cf752c85efeb2
- Size of remote file:
- 3.32 kB
- SHA256:
- e4aecd63efca5c3ba99a2e8e23709b4a72341c969557472b4e06cf1fc300ec7b
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