Text Ranking
Transformers
PyTorch
Safetensors
multilingual
llama_bidirec
text-classification
text
reranker
cross-encoder
retrieval
semantic-search
custom_code
text-embeddings-inference
Instructions to use nvidia/llama-nemotron-rerank-1b-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use nvidia/llama-nemotron-rerank-1b-v2 with Transformers:
# Load model directly from transformers import AutoModelForSequenceClassification model = AutoModelForSequenceClassification.from_pretrained("nvidia/llama-nemotron-rerank-1b-v2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Oliver Holworthy commited on
Commit ·
8fd3e5d
1
Parent(s): 3f42648
Add rope_theta to rope_scaling for transformers 5.4+ compatibility (#14)
Browse files- fix: add rope_theta to rope_scaling for transformers v5.4+ compat (6a2a6e3b4ce116b2b1723a409049e8f44bc5f382)
- config.json +2 -1
config.json
CHANGED
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@@ -37,7 +37,8 @@
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"high_freq_factor": 4.0,
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"low_freq_factor": 1.0,
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"original_max_position_embeddings": 8192,
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-
"rope_type": "llama3"
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},
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"rope_theta": 500000.0,
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"temperature": 1.0,
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"high_freq_factor": 4.0,
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"low_freq_factor": 1.0,
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"original_max_position_embeddings": 8192,
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+
"rope_type": "llama3",
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"rope_theta": 500000.0
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},
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"rope_theta": 500000.0,
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"temperature": 1.0,
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