Instructions to use chenhg8680/mt5-sum-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chenhg8680/mt5-sum-v1 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="chenhg8680/mt5-sum-v1")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("chenhg8680/mt5-sum-v1") model = AutoModelForSeq2SeqLM.from_pretrained("chenhg8680/mt5-sum-v1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer_config.json from chenhg8680/mt5-sum-v1: direct link, hf CLI and curl.
- Browser
- Download file 478 Bytes
-
https://huggingface.co/chenhg8680/mt5-sum-v1/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://chenhg8680/mt5-sum-v1/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/chenhg8680/mt5-sum-v1/resolve/main/tokenizer_config.json
478 Bytes
| { | |
| "additional_special_tokens": null, | |
| "eos_token": "</s>", | |
| "extra_ids": 0, | |
| "model_max_length": 1000000000000000019884624838656, | |
| "name_or_path": "AutoTrain", | |
| "pad_token": "<pad>", | |
| "sp_model_kwargs": {}, | |
| "special_tokens_map_file": "/home/patrick/.cache/torch/transformers/685ac0ca8568ec593a48b61b0a3c272beee9bc194a3c7241d15dcadb5f875e53.f76030f3ec1b96a8199b2593390c610e76ca8028ef3d24680000619ffb646276", | |
| "tokenizer_class": "T5Tokenizer", | |
| "unk_token": "<unk>" | |
| } | |