Instructions to use zeromodels/all-MiniLM-L12-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ZeroModels
How to use zeromodels/all-MiniLM-L12-v2 with ZeroModels:
# pip install -U zeromodels # ZeroModels is pure Keras 3, so pick a backend: "jax", "torch" or "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" from zeromodels import AutoZModel # AutoZModel reads the repo's model_type and loads the matching class. # For a task head use the matching loader, e.g. AutoZMImageClassify / AutoZMDetect / # AutoZMSemanticSegment / AutoZMTextGenerate (see zeromodels.auto). model = AutoZModel.from_weights("zeromodels/all-MiniLM-L12-v2") - Keras
How to use zeromodels/all-MiniLM-L12-v2 with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://zeromodels/all-MiniLM-L12-v2") - sentence-transformers
How to use zeromodels/all-MiniLM-L12-v2 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("zeromodels/all-MiniLM-L12-v2") 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] - Notebooks
- Google Colab
- Kaggle
Download zm_preprocessor.json from zeromodels/all-MiniLM-L12-v2: direct link, hf CLI and curl.
- Browser
- Download file 722 Bytes
-
https://huggingface.co/zeromodels/all-MiniLM-L12-v2/resolve/main/zm_preprocessor.json
- Command line
-
hf download hf://zeromodels/all-MiniLM-L12-v2/zm_preprocessor.json
-
curl -L -o zm_preprocessor.json https://huggingface.co/zeromodels/all-MiniLM-L12-v2/resolve/main/zm_preprocessor.json
722 Bytes
| { | |
| "library_name": "zeromodels", | |
| "preprocessor_module": "zeromodels.sentence_transformers", | |
| "preprocessor_class": "ZMSentenceTransformerTokenizer", | |
| "variant": "all-MiniLM-L12-v2", | |
| "tokenizer_file": "tokenizer.json", | |
| "backbone_type": "bert", | |
| "tokenizer_config": { | |
| "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, | |
| "do_basic_tokenize": true, | |
| "never_split": null, | |
| "tokenizer_class": "BertTokenizer", | |
| "model_max_length": 512 | |
| }, | |
| "sentence_transformer_config": { | |
| "max_seq_length": 128, | |
| "do_lower_case": false | |
| } | |
| } | |