Text Classification
Transformers
PyTorch
TensorBoard
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use HanBi/my_awesome_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use HanBi/my_awesome_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="HanBi/my_awesome_model")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("HanBi/my_awesome_model") model = AutoModelForSequenceClassification.from_pretrained("HanBi/my_awesome_model") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 2
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 267855533
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:f579168d91c77ba9329df59dc1b97bf8940be319dcbb19048cbb6cdc37a3d422
|
| 3 |
size 267855533
|
runs/Jun22_15-23-57_96f896cd58b0/events.out.tfevents.1687447514.96f896cd58b0.2226.0
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 sha256:9d51a532d04c2eb4d925455d524966f1364edebd6552f920065af74c9aa97a9e
|
| 3 |
+
size 4655
|