Instructions to use mgh6/temp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mgh6/temp with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="mgh6/temp")# Load model directly from transformers import AutoTokenizer, AutoModelForMaskedLM tokenizer = AutoTokenizer.from_pretrained("mgh6/temp") model = AutoModelForMaskedLM.from_pretrained("mgh6/temp") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 1500
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 136048297
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:e2aaeea04f119cc934000b277d5dbbbd74ef5f6768a2dc3be86bd0e77c590bb0
|
| 3 |
size 136048297
|
runs/Jul28_16-14-35_0b9a212978fe/events.out.tfevents.1690560878.0b9a212978fe.1880.1
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 sha256:2a0465979b31293b1fb2ae5cd4b1d8bd7d2cb2df0b36f8fbcfb43e5a6421f6ba
|
| 3 |
+
size 4880
|