Instructions to use rxdtech/potion-code-16M-v2-onnx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Model2Vec
How to use rxdtech/potion-code-16M-v2-onnx with Model2Vec:
from model2vec import StaticModel model = StaticModel.from_pretrained("rxdtech/potion-code-16M-v2-onnx") embeddings = model.encode(["It's dangerous to go alone!", "It's a secret to everybody."]) print(embeddings.shape) - sentence-transformers
How to use rxdtech/potion-code-16M-v2-onnx with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("rxdtech/potion-code-16M-v2-onnx") 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
File size: 379 Bytes
50b6d31 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | {
"backend": "tokenizers",
"clean_up_tokenization_spaces": false,
"max_length": 512,
"model_max_length": 512,
"pad_to_multiple_of": null,
"pad_token": "[pad]",
"pad_token_type_id": 0,
"padding_side": "right",
"stride": 0,
"tokenizer_class": "TokenizersBackend",
"truncation_side": "right",
"truncation_strategy": "longest_first",
"unk_token": "[UNK]"
}
|