Text Ranking
Transformers
Safetensors
multilingual
t5gemma2
text2text-generation
reranker
encoder-decoder
FBNL
Retrieval
RAG
Instructions to use KaLM-Embedding/KaLM-Reranker-V1-Nano with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use KaLM-Embedding/KaLM-Reranker-V1-Nano with Transformers:
# Load model directly from transformers import AutoProcessor, AutoModelForMultimodalLM processor = AutoProcessor.from_pretrained("KaLM-Embedding/KaLM-Reranker-V1-Nano") model = AutoModelForMultimodalLM.from_pretrained("KaLM-Embedding/KaLM-Reranker-V1-Nano") - Notebooks
- Google Colab
- Kaggle
| [build-system] | |
| requires = ["setuptools>=64"] | |
| build-backend = "setuptools.build_meta" | |
| [project] | |
| name = "kalm-t5gemma2-vllm-plugin" | |
| version = "0.1.0" | |
| description = "vLLM 0.19.1 adapter for KaLM-Reranker-V1-Nano" | |
| readme = "README.md" | |
| requires-python = ">=3.12,<3.13" | |
| license = {text = "Apache-2.0"} | |
| dependencies = [ | |
| "transformers==5.6.2", | |
| "vllm==0.19.1", | |
| ] | |
| [project.optional-dependencies] | |
| online = [ | |
| "fastapi>=0.136,<0.137", | |
| "uvicorn>=0.46,<0.47", | |
| ] | |
| [project.entry-points."vllm.general_plugins"] | |
| kalm_t5gemma2 = "kalm_t5gemma2_vllm_plugin.register:register" | |
| [project.scripts] | |
| kalm-vllm-rerank = "kalm_t5gemma2_vllm_plugin.cli:main" | |
| kalm-vllm-serve = "kalm_t5gemma2_vllm_plugin.server:main" | |
| kalm-vllm-client = "kalm_t5gemma2_vllm_plugin.client:main" | |
| [tool.setuptools.packages.find] | |
| where = ["src"] | |