Transformers
PyTorch
English
bart
text2text-generation
onprem
llm
ai
ml
llmops
postgresml
pgvector
vmware
tanzu
Instructions to use tanzuhuggingface/dev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tanzuhuggingface/dev with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("tanzuhuggingface/dev") model = AutoModelForSeq2SeqLM.from_pretrained("tanzuhuggingface/dev", device_map="auto") - Notebooks
- Google Colab
- Kaggle
| language: | |
| - en | |
| thumbnail: "https://blogs.vmware.com/cloudprovider/files/2021/09/logo-vmware-tanzu-square-Header.png" | |
| tags: | |
| - onprem | |
| - llm | |
| - ai | |
| - ml | |
| - llmops | |
| - postgresml | |
| - pgvector | |
| - vmware | |
| - tanzu | |
| datasets: | |
| - dataset1 | |
| - dataset2 | |
| metrics: | |
| - metric1 | |
| - metric2 | |
| # Model Card for dev | |
| This is a sample Tanzu model which was generated for demonstration purposes. | |
| ## Model Details | |
| **Model Description:** | |
| - **Developed by:** : tanzuhuggingface | |
| - **Model type** : Open Generative QA | |
| - **Language(s) (NLP)** : English | |
| - **Finetuned from model** : distilbert-base-cased-distilled-squad | |