Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use philschmid/MiniLMv2-L6-H384-sst2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use philschmid/MiniLMv2-L6-H384-sst2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="philschmid/MiniLMv2-L6-H384-sst2")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("philschmid/MiniLMv2-L6-H384-sst2") model = AutoModelForSequenceClassification.from_pretrained("philschmid/MiniLMv2-L6-H384-sst2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#3
by SFconvertbot - opened
- .gitattributes +1 -0
- model.safetensors +3 -0
.gitattributes
CHANGED
|
@@ -26,3 +26,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
|
|
| 26 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 27 |
*.zstandard filter=lfs diff=lfs merge=lfs -text
|
| 28 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
|
|
|
|
|
| 26 |
*.zip filter=lfs diff=lfs merge=lfs -text
|
| 27 |
*.zstandard filter=lfs diff=lfs merge=lfs -text
|
| 28 |
*tfevents* filter=lfs diff=lfs merge=lfs -text
|
| 29 |
+
model.safetensors filter=lfs diff=lfs merge=lfs -text
|
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:30c0ba413f51db1bf6a21cbb045a1a10e146bd295e21e3b65d6ecf5df913d24d
|
| 3 |
+
size 121199344
|