Feature Extraction
Transformers
Safetensors
scripture_genome_head
scripture
multilingual
information-retrieval
semantic-search
genome-regression
frozen-encoder
custom-head
custom_code
Instructions to use chainuser1/Scripture_Genome_Multilingual_Head_BGE_M3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use chainuser1/Scripture_Genome_Multilingual_Head_BGE_M3 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="chainuser1/Scripture_Genome_Multilingual_Head_BGE_M3", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("chainuser1/Scripture_Genome_Multilingual_Head_BGE_M3", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 899 Bytes
d69f154 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 | {
"rows": 32,
"inputs": "seeded synthetic normalized vectors; not a retrieval benchmark",
"variants": {
"fp32": {
"source_tensor_values_preserved": true,
"source_loader_max_abs_delta": 0.0,
"max_abs_delta_vs_fp32": 0.0,
"mean_abs_delta_vs_fp32": 0.0
},
"fp16": {
"source_tensor_values_preserved": true,
"source_loader_max_abs_delta": 0.0,
"max_abs_delta_vs_fp32": 0.00044864416122436523,
"mean_abs_delta_vs_fp32": 2.0774701624759473e-05
},
"int8": {
"source_tensor_values_preserved": true,
"source_loader_max_abs_delta": 0.0,
"max_abs_delta_vs_fp32": 0.017965853214263916,
"mean_abs_delta_vs_fp32": 0.000984748243354261
}
},
"automodel_from_pretrained": "passed locally with custom-code trust",
"base_encoder_execution": "not tested by this head-only conversion"
}
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