Instructions to use Mouserat/titlerat2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Mouserat/titlerat2 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="Mouserat/titlerat2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Mouserat/titlerat2") model = AutoModelForSeq2SeqLM.from_pretrained("Mouserat/titlerat2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from Mouserat/titlerat2: direct link, hf CLI and curl.
- Browser
- Download file 16.4 MB
-
https://huggingface.co/Mouserat/titlerat2/resolve/main/tokenizer.json
- Command line
-
hf download hf://Mouserat/titlerat2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/Mouserat/titlerat2/resolve/main/tokenizer.json
16.4 MB
- Xet hash:
- b0a9acbb7a022739f92854adb275ed23a770585800d93e67033cc026581c7878
- Size of remote file:
- 16.4 MB
- SHA256:
- 1cfd65d3df865f6cb8478c421365ffb6ba3920d1674776eefb3e0bcf6cf18bd8
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