Instructions to use shed-e/Summary with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shed-e/Summary 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="shed-e/Summary")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("shed-e/Summary") model = AutoModelForSeq2SeqLM.from_pretrained("shed-e/Summary", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from shed-e/Summary: direct link, hf CLI and curl.
- Browser
- Download file 74 Bytes
-
https://huggingface.co/shed-e/Summary/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://shed-e/Summary/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/shed-e/Summary/resolve/main/special_tokens_map.json
74 Bytes
| { | |
| "eos_token": "</s>", | |
| "pad_token": "<pad>", | |
| "unk_token": "<unk>" | |
| } | |