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
Download quantization_config.json from chainuser1/Scripture_Genome_Multilingual_Head_BGE_M3: direct link, hf CLI and curl.
- Browser
- Download file 269 Bytes
-
https://huggingface.co/chainuser1/Scripture_Genome_Multilingual_Head_BGE_M3/resolve/main/quantization_config.json
- Command line
-
hf download hf://chainuser1/Scripture_Genome_Multilingual_Head_BGE_M3/quantization_config.json
-
curl -L -o quantization_config.json https://huggingface.co/chainuser1/Scripture_Genome_Multilingual_Head_BGE_M3/resolve/main/quantization_config.json
269 Bytes
| { | |
| "file": "head_int8.safetensors", | |
| "scope": "head only; base is separate and unchanged", | |
| "weight_formula": "w[i].float() * scale[i][:, None]", | |
| "bias_dtype": "float32", | |
| "runtime": "inference.py dequantizes to float32; no INT8 acceleration is claimed" | |
| } | |