Summarization
Transformers
PyTorch
Enawené-Nawé
pegasus
text2text-generation
Trained with AutoTrain
Prompt Generation
prompt-generator
text generator
Instructions to use SamAct/PromptGeneration-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SamAct/PromptGeneration-base 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="SamAct/PromptGeneration-base")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("SamAct/PromptGeneration-base") model = AutoModelForSeq2SeqLM.from_pretrained("SamAct/PromptGeneration-base") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -12,7 +12,7 @@ datasets:
|
|
| 12 |
co2_eq_emissions:
|
| 13 |
emissions: 2.4412207269598545
|
| 14 |
---
|
| 15 |
-
|
| 16 |
## Usecase
|
| 17 |
1. Prompt Generation.
|
| 18 |
2. Title Generation.
|
|
|
|
| 12 |
co2_eq_emissions:
|
| 13 |
emissions: 2.4412207269598545
|
| 14 |
---
|
| 15 |
+
## If you like this model you can by me a coffee here: https://www.buymeacoffee.com/SamAct
|
| 16 |
## Usecase
|
| 17 |
1. Prompt Generation.
|
| 18 |
2. Title Generation.
|