Instructions to use NbAiLabArchive/test_w5_long_roberta_tokenizer_adafactor with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NbAiLabArchive/test_w5_long_roberta_tokenizer_adafactor with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NbAiLabArchive/test_w5_long_roberta_tokenizer_adafactor")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NbAiLabArchive/test_w5_long_roberta_tokenizer_adafactor") model = AutoModelForMaskedLM.from_pretrained("NbAiLabArchive/test_w5_long_roberta_tokenizer_adafactor") - Notebooks
- Google Colab
- Kaggle
Saving weights and logs of step 65000
Browse files
events.out.tfevents.1639912087.t1v-n-4e27a527-w-0.1954459.0.v2
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 sha256:1ff7ee25142b471d6bc8fb7b941c626c2f036c72fe25cbad877b8cec91b99483
|
| 3 |
+
size 8385363
|
flax_model.msgpack
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 498796983
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:1c7e83d9ac34279cfad1511dd0c711417853ec8ec3449309121e413bd44ed230
|
| 3 |
size 498796983
|