Summarization
Transformers
PyTorch
t5
text2text-generation
Generated from Trainer
text-generation-inference
Instructions to use chakochen/t5-small-destination-inference with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chakochen/t5-small-destination-inference 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="chakochen/t5-small-destination-inference")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("chakochen/t5-small-destination-inference") model = AutoModelForSeq2SeqLM.from_pretrained("chakochen/t5-small-destination-inference", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 19500
Browse files- pytorch_model.bin +1 -1
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 242070230
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:6f7ec6f701cd2252d02eca9656cf173c09fd75e4df04ff912c404be6b7b93e00
|
| 3 |
size 242070230
|