Text Classification
Transformers
PyTorch
TensorBoard
ONNX
distilbert
Generated from Trainer
text-embeddings-inference
Instructions to use ziq/ingbetic with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ziq/ingbetic with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="ziq/ingbetic")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("ziq/ingbetic") model = AutoModelForSequenceClassification.from_pretrained("ziq/ingbetic", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, step 1300
Browse files
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 267852461
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:0f32495b22dd7fc39e077b6548826cbe8f567cac2ad8878c6cd421ff6d40cbb8
|
| 3 |
size 267852461
|
runs/Jun07_15-58-55_ny736lt2rd/events.out.tfevents.1686153639.ny736lt2rd.180.0
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 sha256:386477dafdb3a16d9fd2384178a986556fa2f65d1fcfcfc25e20a920100e6d0b
|
| 3 |
+
size 31401
|