Sentence Similarity
Transformers
Safetensors
English
Arabic
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mentee_embed
feature-extraction
embeddings
retrieval
contrastive-learning
multilingual
from-scratch
custom_code
Instructions to use MenteEAI/mentee-embed-v3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use MenteEAI/mentee-embed-v3 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("MenteEAI/mentee-embed-v3", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 787 Bytes
726d37e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 | """
__init__.py — makes hf_hub a proper package and registers
MenteeEmbedConfig + MenteeEmbedModel with the HuggingFace Auto classes.
When HF loads a repo with trust_remote_code=True it imports this file first,
which triggers the AutoModel/AutoConfig registration automatically.
"""
from .configuration_mentee import MenteeEmbedConfig
from .modeling_mentee import MenteeEmbedModel
from .tokenization_mentee import MenteeTokenizer
from transformers import AutoConfig, AutoModel, AutoTokenizer
AutoConfig.register("mentee_embed", MenteeEmbedConfig)
AutoModel.register(MenteeEmbedConfig, MenteeEmbedModel)
AutoTokenizer.register(MenteeEmbedConfig, slow_tokenizer_class=None, fast_tokenizer_class=MenteeTokenizer)
__all__ = ["MenteeEmbedConfig", "MenteeEmbedModel", "MenteeTokenizer"]
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