Instructions to use ssdatar/output with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ssdatar/output with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ssdatar/output") model = AutoModelForSeq2SeqLM.from_pretrained("ssdatar/output", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 1500
Browse files
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 557912620
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:2755a402f8a7707a992620fbd1f01049d08012ded13ae268fa8055de6332bddf
|
| 3 |
size 557912620
|
runs/Nov26_06-02-42_fc26544c7819/events.out.tfevents.1700978575.fc26544c7819.239.0
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 sha256:2dc8a9a74916d8b8917b4e69b86a9b95da8a2e8976b4c60566902c3fe98ba050
|
| 3 |
+
size 6005
|