Sentence Similarity
sentence-transformers
PyTorch
Transformers
xlm-roberta
feature-extraction
text-embeddings-inference
Instructions to use gnail/hamlet-distill-st with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use gnail/hamlet-distill-st with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("gnail/hamlet-distill-st") sentences = [ "That is a happy person", "That is a happy dog", "That is a very happy person", "Today is a sunny day" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4] - Transformers
How to use gnail/hamlet-distill-st with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("gnail/hamlet-distill-st") model = AutoModel.from_pretrained("gnail/hamlet-distill-st", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Adding `safetensors` variant of this model
#1
by SFconvertbot - opened
- 2_Dense/model.safetensors +3 -0
- model.safetensors +3 -0
2_Dense/model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:39888cd21f1bc68357f937ad1ccfd73e6334c7c0f0efa2e570418f398f38310e
|
| 3 |
+
size 9437304
|
model.safetensors
ADDED
|
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:dae29f2b8e52eeb65070aeca330f8881ed827f1dd2ec7af4c186160757c4958e
|
| 3 |
+
size 1109838736
|