Feature Extraction
Transformers
Safetensors
English
qwen2
embeddings
base-model
qwen
text-embeddings-inference
Instructions to use ssmits/Qwen2-7B-embed-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ssmits/Qwen2-7B-embed-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ssmits/Qwen2-7B-embed-base")# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ssmits/Qwen2-7B-embed-base") model = AutoModel.from_pretrained("ssmits/Qwen2-7B-embed-base", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload 1_Pooling_config.json
Browse files
1_Pooling/1_Pooling_config.json
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{
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"word_embedding_dimension": 4096,
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"pooling_mode_cls_token": false,
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"pooling_mode_mean_tokens": false,
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"pooling_mode_max_tokens": false,
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"pooling_mode_mean_sqrt_len_tokens": false,
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"pooling_mode_weightedmean_tokens": false,
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"pooling_mode_lasttoken": true,
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"include_prompt": true
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}
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