Sentence Similarity
Transformers
Safetensors
Ganda
sagepond_un_model
feature-extraction
luganda
embeddings
sentence-embeddings
semantic-search
research
custom_code
Eval Results (legacy)
Instructions to use sagepond/embedding-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use sagepond/embedding-small with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("sagepond/embedding-small", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download config.json from sagepond/embedding-small: direct link, hf CLI and curl.
- Browser
- Download file 650 Bytes
-
https://huggingface.co/sagepond/embedding-small/resolve/main/config.json
- Command line
-
hf download hf://sagepond/embedding-small/config.json
-
curl -L -o config.json https://huggingface.co/sagepond/embedding-small/resolve/main/config.json
650 Bytes
| { | |
| "architectures": [ | |
| "UnModel" | |
| ], | |
| "auto_map": { | |
| "AutoConfig": "ganda_config.UnModelConfig", | |
| "AutoModel": "ganda_model.UnModel", | |
| "AutoTokenizer": [ | |
| "tokenization_un_model.UnModelTokenizer", | |
| null | |
| ] | |
| }, | |
| "bos_token_id": 2, | |
| "dropout": 0.1, | |
| "dtype": "float32", | |
| "embedding_dim": 3072, | |
| "eos_token_id": 3, | |
| "hidden_act": "relu", | |
| "hidden_size": 768, | |
| "intermediate_size": 3072, | |
| "max_position_embeddings": 600, | |
| "model_type": "sagepond_un_model", | |
| "num_attention_heads": 16, | |
| "num_hidden_layers": 12, | |
| "pad_token_id": 0, | |
| "transformers_version": "5.20.2", | |
| "unk_token_id": 1, | |
| "vocab_size": 40000 | |
| } | |