Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
text-embeddings-inference
Instructions to use jayavibhav/roberta-classification-10ksamples with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use jayavibhav/roberta-classification-10ksamples with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="jayavibhav/roberta-classification-10ksamples")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("jayavibhav/roberta-classification-10ksamples") model = AutoModelForSequenceClassification.from_pretrained("jayavibhav/roberta-classification-10ksamples", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit ·
02dc438
1
Parent(s): 2a3b5c5
Training in progress, epoch 1
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 498657649
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:b286d351ee430c1abca94351dd0cef44f47a43188fdc7053e50d1438fdd0c957
|
| 3 |
size 498657649
|
runs/Aug09_09-07-16_ac8c734d6f74/events.out.tfevents.1691572043.ac8c734d6f74.18761.0
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:76b937581f69c55581851bc354f197369ab154b5b8a5d254668b356e156f8cac
|
| 3 |
+
size 4853
|
training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 4027
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:78f31e768ed9b844ef038fb256d6871d0bd8f9a316cce9032d2421f0235277ed
|
| 3 |
size 4027
|