Instructions to use Nicolas-BZRD/mt0-base_dialogsum_Mistral-7B-Instruct-v0.2_uld_loss with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nicolas-BZRD/mt0-base_dialogsum_Mistral-7B-Instruct-v0.2_uld_loss with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Nicolas-BZRD/mt0-base_dialogsum_Mistral-7B-Instruct-v0.2_uld_loss") model = AutoModelForSeq2SeqLM.from_pretrained("Nicolas-BZRD/mt0-base_dialogsum_Mistral-7B-Instruct-v0.2_uld_loss", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5d191c62ff20c895dd74f93a0672150831bf9733292f12bff4f3517de24eedde
- Size of remote file:
- 2.33 GB
- SHA256:
- 9fd4ef56bed3981d2b262c5b61e5d5d0505890fd83b9c4f54c658b0307fbcecc
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