Instructions to use chakochen/mt5-destination-inference with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chakochen/mt5-destination-inference 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="chakochen/mt5-destination-inference")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("chakochen/mt5-destination-inference") model = AutoModelForSeq2SeqLM.from_pretrained("chakochen/mt5-destination-inference", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download generation_config.json from chakochen/mt5-destination-inference: direct link, hf CLI and curl.
- Browser
- Download file 112 Bytes
-
https://huggingface.co/chakochen/mt5-destination-inference/resolve/main/generation_config.json
- Command line
-
hf download hf://chakochen/mt5-destination-inference/generation_config.json
-
curl -L -o generation_config.json https://huggingface.co/chakochen/mt5-destination-inference/resolve/main/generation_config.json
112 Bytes
| { | |
| "decoder_start_token_id": 0, | |
| "eos_token_id": 1, | |
| "pad_token_id": 0, | |
| "transformers_version": "4.33.2" | |
| } | |