Instructions to use fanjiang98/STDPR-NQ with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fanjiang98/STDPR-NQ with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="fanjiang98/STDPR-NQ")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("fanjiang98/STDPR-NQ") model = AutoModel.from_pretrained("fanjiang98/STDPR-NQ", 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 sha256:49a278ec9513217205b856348936de96b9ea57893eba7841a1c515aa3a906993
|
| 3 |
+
size 437955512
|