Feature Extraction
Transformers
PyTorch
Safetensors
bert
mteb
Eval Results (legacy)
text-embeddings-inference
Instructions to use infgrad/stella-base-zh with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use infgrad/stella-base-zh with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="infgrad/stella-base-zh")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("infgrad/stella-base-zh") model = AutoModel.from_pretrained("infgrad/stella-base-zh", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#2
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 sha256:48b9eb9ff0ccd54d5c2c7cdeed7e5d42a3a16568f16aa44f2167c867f76fe300
|
| 3 |
+
size 205352232
|