Instructions to use ArchCoder/fine-tuned-bart-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ArchCoder/fine-tuned-bart-large 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="ArchCoder/fine-tuned-bart-large")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ArchCoder/fine-tuned-bart-large") model = AutoModelForSeq2SeqLM.from_pretrained("ArchCoder/fine-tuned-bart-large") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 43eb410996fbcd2edcc0040f9631566f8409d900a4ae7fc5cf523d051e7d3ca5
- Size of remote file:
- 1.63 GB
- SHA256:
- 1cff490caa3dc1280ec7c6063779f69195d151cdc9e4fa30917f27e553b3c40f
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.