Instructions to use jparmet/topic-hf-dropout with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jparmet/topic-hf-dropout with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jparmet/topic-hf-dropout")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jparmet/topic-hf-dropout") model = AutoModelForSequenceClassification.from_pretrained("jparmet/topic-hf-dropout", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Jeffrey P commited on
Commit ·
583eeee
1
Parent(s): 78ff39f
Training in progress, step 6000
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 669541493
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:59bd26f9ec1a8438330e1200b4f7b58ce654a44a2c49653da3411b966d226229
|
| 3 |
size 669541493
|
runs/Jul31_19-40-16_14a542b97615/events.out.tfevents.1690832418.14a542b97615.4560.10
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:f20e1425a259b6881281a7295cc6957bac97cf6eb7359aab5fb432b8d786c8d0
|
| 3 |
+
size 6988
|