Instructions to use Cournane/roberta-base-labels-Upper_fabric with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Cournane/roberta-base-labels-Upper_fabric with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="Cournane/roberta-base-labels-Upper_fabric", device_map="auto")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("Cournane/roberta-base-labels-Upper_fabric") model = AutoModelForSequenceClassification.from_pretrained("Cournane/roberta-base-labels-Upper_fabric", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- model.safetensors +3 -0
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:aa41ba583b02b19fccb624eca213139fa591ebbdbb22bda03c664e9602de389d
|
| 3 |
+
size 498632404
|