Instructions to use abigailp/m3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use abigailp/m3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="abigailp/m3")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("abigailp/m3") model = AutoModelForSequenceClassification.from_pretrained("abigailp/m3", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Training in progress, epoch 11
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 sha256:1e9803c4b6d62761826543128ec70e87004f649a639ab5cebcc451281efb4399
|
| 3 |
size 267855533
|
runs/Jan31_14-03-22_b152d93c994a/events.out.tfevents.1675173811.b152d93c994a.371.3
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 sha256:59ef05438624a8786780af5420926ae0a37224026ae0e8fd3f01e3100862e892
|
| 3 |
+
size 7818
|