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
metadata
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