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 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 267855533
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:68895f61af2c62fddec29b0b5c45d89970fd80ad6b4188ea3792a7883ffa243b
|
| 3 |
size 267855533
|
runs/Jun22_15-23-57_96f896cd58b0/events.out.tfevents.1687447514.96f896cd58b0.2226.0
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:26f69e26bfd40fcad2b102df507c1942b28d70d62daeb0df1fadc8a7587ac544
|
| 3 |
+
size 4332
|
training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 3963
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:643638c5e7c9ebec3f974f883026e1cc431b014d6a2f9b89749462e5f673c820
|
| 3 |
size 3963
|