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: 1,368 Bytes
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"format_version": 1,
"production_model": {
"track": "question",
"hidden": 4096,
"architecture": [
1024,
4096,
568
],
"activation": "GELU",
"output_activation": "Sigmoid",
"checkpoint_sha256": "5a68ef73167f48899c927dfb5e25dfe8ff50d0b8e8310cd6f3ff3c93b8bf9952"
},
"encoder": {
"model": "BAAI/bge-m3",
"revision": "5617a9f61b028005a4858fdac845db406aefb181",
"flagembedding_version": "1.4.2",
"max_length": 512,
"pooling": "normalized CLS"
},
"retrieval": {
"pipeline": "Experiment D",
"candidate_language": "english",
"candidate_generation": [
"dense top 200",
"sparse top 200",
"genome top 200"
],
"candidate_union": true,
"colbert": "BGE-M3 MaxSim over the candidate union",
"weights": {
"dense": 0.28,
"sparse": 0.14,
"colbert": 0.28,
"genome": 0.3
},
"score_normalization": "sample z-score over candidate union",
"family_retrieval_weights": {
"B": 0.75,
"I": 0.5,
"N": 0.5,
"Q": 0.0,
"T": 0.75,
"U": 0.75,
"default": 1.0
},
"family_q_excluded": true,
"default_top_k": 20
},
"validation": {
"split": "val",
"question_ids": 250,
"rows": 2000,
"report_sha256": "6f87e359c3717660d6fee2c9c8caf3bde0543d22b6ac2a2d8379dd9aabb70f91"
}
}
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