Instructions to use NBRZ/bert-trainer-8b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NBRZ/bert-trainer-8b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="NBRZ/bert-trainer-8b")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("NBRZ/bert-trainer-8b") model = AutoModelForMaskedLM.from_pretrained("NBRZ/bert-trainer-8b", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 9000
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 438130617
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:793304d6cb2ae48465d24978d64f215ef2248a98e63281a04bf924e5d8bbdd10
|
| 3 |
size 438130617
|
runs/Jun14_13-19-06_dl/events.out.tfevents.1686763154.dl.596308.0
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 sha256:4afac8f6a8a5172d3a2d70db66cfc36b5e10425a4bab63f4a7e685e4c87027c7
|
| 3 |
+
size 22678
|