Instructions to use nanopass/test-model-fe with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use nanopass/test-model-fe with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("nanopass/test-model-fe") 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
Download tokenizer_config.json from nanopass/test-model-fe: direct link, hf CLI and curl.
- Browser
- Download file 383 Bytes
-
https://huggingface.co/nanopass/test-model-fe/resolve/main/tokenizer_config.json
- Command line
-
hf download hf://nanopass/test-model-fe/tokenizer_config.json
-
curl -L -o tokenizer_config.json https://huggingface.co/nanopass/test-model-fe/resolve/main/tokenizer_config.json
383 Bytes
| {"do_lower_case": true, "unk_token": "[UNK]", "sep_token": "[SEP]", "pad_token": "[PAD]", "cls_token": "[CLS]", "mask_token": "[MASK]", "tokenize_chinese_chars": true, "strip_accents": null, "special_tokens_map_file": null, "name_or_path": "nreimers/MiniLM-L6-H384-uncased", "do_basic_tokenize": true, "never_split": null, "tokenizer_class": "BertTokenizer", "model_max_length": 512} |