Instructions to use binqiangliu/EmbeddingModelallMiniLML6v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use binqiangliu/EmbeddingModelallMiniLML6v2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="binqiangliu/EmbeddingModelallMiniLML6v2")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("binqiangliu/EmbeddingModelallMiniLML6v2") model = AutoModel.from_pretrained("binqiangliu/EmbeddingModelallMiniLML6v2") - Notebooks
- Google Colab
- Kaggle
Commit ·
437ef2c
1
Parent(s): f679e95
Upload pytorch_model.bin with huggingface_hub
Browse files- pytorch_model.bin +3 -0
pytorch_model.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:c3a85f238711653950f6a79ece63eb0ea93d76f6a6284be04019c53733baf256
|
| 3 |
+
size 90888945
|