Translation
Transformers
ONNX
Transformers.js
English
t5
text2text-generation
cron
scheduling
cronlm
Instructions to use pavstev/cronlm with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use pavstev/cronlm with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" 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("translation", model="pavstev/cronlm")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("pavstev/cronlm") model = AutoModelForSeq2SeqLM.from_pretrained("pavstev/cronlm") - Transformers.js
How to use pavstev/cronlm with Transformers.js:
// npm i @huggingface/transformers import { pipeline } from '@huggingface/transformers'; // Allocate pipeline const pipe = await pipeline('translation', 'pavstev/cronlm'); - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- b84361b21fa9220596b29d19fbbe1bbd6fd0f4aab150f252c6940398626c457d
- Size of remote file:
- 12.1 MB
- SHA256:
- de6147c5fb4ebb3cb7a5424c4f9dcb6983dec86d6e1f15085a2268b704088920
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.