Instructions to use cp500/body_part_annotator with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use cp500/body_part_annotator with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="cp500/body_part_annotator")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("cp500/body_part_annotator") model = AutoModelForTokenClassification.from_pretrained("cp500/body_part_annotator") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 1
Browse files- pytorch_model.bin +1 -1
- training_args.bin +1 -1
pytorch_model.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 735099049
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:4d9589d345afcd270ff52f071c12326f443dbdff8d9407c0c087a532d34d1636
|
| 3 |
size 735099049
|
training_args.bin
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 4091
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:d2886a0d30ba8a73e420448b4d7f6bb50b6f468f7319638a2ac2d509b80d8d51
|
| 3 |
size 4091
|