Instructions to use paulh27/xsum_aligned_smallT5_cont3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use paulh27/xsum_aligned_smallT5_cont3 with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("paulh27/xsum_aligned_smallT5_cont3") model = AutoModelForSeq2SeqLM.from_pretrained("paulh27/xsum_aligned_smallT5_cont3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 30000
Browse files
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 242041896
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:26ad3156b0302571d4c0ef5415c88599bde95d7dfc83caf6d84dad6885d1c948
|
| 3 |
size 242041896
|
runs/Apr30_19-39-54_nlpg00.cs.washington.edu/events.out.tfevents.1714531487.nlpg00.cs.washington.edu.1045439.0
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 sha256:2cad126db7c4b745d9a31257ab7e151a7c4a1d571e755ac37be2b56bb6ec5bfb
|
| 3 |
+
size 13761
|