Summarization
Transformers
PyTorch
Safetensors
longt5
text2text-generation
long
title generation
Eval Results (legacy)
Instructions to use Joemgu/mlong-t5-large-sumstew with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Joemgu/mlong-t5-large-sumstew 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="Joemgu/mlong-t5-large-sumstew")# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("Joemgu/mlong-t5-large-sumstew") model = AutoModelForSeq2SeqLM.from_pretrained("Joemgu/mlong-t5-large-sumstew", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload pytorch_model.bin
Browse files- pytorch_model.bin +2 -2
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:ca16eb2b14609961b1404483c03c7213a6e80e4d8df8d5ab915176526dbfb436
|
| 3 |
+
size 4970011106
|