Feature Extraction
sentence-transformers
Safetensors
Vietnamese
English
bert
sentence-similarity
qdrant
vietnamese
tourist-notebook
text-embeddings-inference
Instructions to use lmtri0312/tramy-encoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use lmtri0312/tramy-encoder with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("lmtri0312/tramy-encoder") sentences = [ "The weather is lovely today.", "It's so sunny outside!", "He drove to the stadium." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [3, 3] - Notebooks
- Google Colab
- Kaggle
Update tokenizer_config.json
Browse files- tokenizer_config.json +4 -5
tokenizer_config.json
CHANGED
|
@@ -1,12 +1,11 @@
|
|
| 1 |
{
|
|
|
|
| 2 |
"bos_token": "<s>",
|
| 3 |
-
"clean_up_tokenization_spaces": true,
|
| 4 |
"cls_token": "<s>",
|
| 5 |
"eos_token": "</s>",
|
| 6 |
-
"mask_token": "<mask >",
|
| 7 |
-
"model_max_length": 512,
|
| 8 |
"pad_token": "<pad>",
|
| 9 |
"sep_token": "</s>",
|
| 10 |
-
"
|
| 11 |
-
"
|
|
|
|
| 12 |
}
|
|
|
|
| 1 |
{
|
| 2 |
+
"tokenizer_class": "PreTrainedTokenizerFast",
|
| 3 |
"bos_token": "<s>",
|
|
|
|
| 4 |
"cls_token": "<s>",
|
| 5 |
"eos_token": "</s>",
|
|
|
|
|
|
|
| 6 |
"pad_token": "<pad>",
|
| 7 |
"sep_token": "</s>",
|
| 8 |
+
"unk_token": "<unk>",
|
| 9 |
+
"model_max_length": 512,
|
| 10 |
+
"clean_up_tokenization_spaces": true
|
| 11 |
}
|