Sentence Similarity
sentence-transformers
Safetensors
Transformers
English
echo
feature-extraction
echo-dsrn
linear-complexity
recurrent-hybrid
custom_code
Instructions to use ethicalabs/Echo-DSRN-v0.1.3-Embed-Exp with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use ethicalabs/Echo-DSRN-v0.1.3-Embed-Exp with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("ethicalabs/Echo-DSRN-v0.1.3-Embed-Exp", trust_remote_code=True) 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 ethicalabs/Echo-DSRN-v0.1.3-Embed-Exp with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("ethicalabs/Echo-DSRN-v0.1.3-Embed-Exp", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
| { | |
| "backend": "tokenizers", | |
| "bos_token": "<s>", | |
| "clean_up_tokenization_spaces": false, | |
| "eos_token": "<|endoftext|>", | |
| "extra_special_tokens": [ | |
| "<tool_call>", | |
| "</tool_call>", | |
| "<tool_response>", | |
| "</tool_response>", | |
| "<tools>", | |
| "</tools>" | |
| ], | |
| "fix_mistral_regex": true, | |
| "is_local": true, | |
| "legacy": false, | |
| "max_length": 2048, | |
| "model_max_length": 2048, | |
| "pad_to_multiple_of": null, | |
| "pad_token": "<|endoftext|>", | |
| "pad_token_type_id": 0, | |
| "padding_side": "left", | |
| "sp_model_kwargs": {}, | |
| "stride": 0, | |
| "tokenizer_class": "TokenizersBackend", | |
| "truncation_side": "right", | |
| "truncation_strategy": "longest_first", | |
| "unk_token": "<unk>", | |
| "use_default_system_prompt": false | |
| } |