Text Classification
Transformers
Safetensors
German
llama
feature-extraction
reranker
cross-encoder
german
retrieval
rag
on-prem
text-embeddings-inference
Instructions to use keyvan-ai/Mankei-326M-Reranker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use keyvan-ai/Mankei-326M-Reranker with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="keyvan-ai/Mankei-326M-Reranker")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("keyvan-ai/Mankei-326M-Reranker") model = AutoModel.from_pretrained("keyvan-ai/Mankei-326M-Reranker", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download benchmark.png from keyvan-ai/Mankei-326M-Reranker: direct link, hf CLI and curl.
- Browser
- Download file 286 kB
-
https://huggingface.co/keyvan-ai/Mankei-326M-Reranker/resolve/main/benchmark.png
- Command line
-
hf download hf://keyvan-ai/Mankei-326M-Reranker/benchmark.png
-
curl -L -o benchmark.png https://huggingface.co/keyvan-ai/Mankei-326M-Reranker/resolve/main/benchmark.png
286 kB

- Xet hash:
- 5b29ed9b4d72988c6de5b85ba6b939f5c599ba41560b302cead9cae425b71524
- Size of remote file:
- 286 kB
- SHA256:
- 940b34c14668ef54049eff00923992416b50972d6e5781f0344b23feb9f34752
·
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