Text Classification
Transformers
Safetensors
English
qwen3
code
reward-model
multilingual
text-embeddings-inference
Instructions to use project-themis/Themis-RM-14B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use project-themis/Themis-RM-14B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="project-themis/Themis-RM-14B")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("project-themis/Themis-RM-14B") model = AutoModelForSequenceClassification.from_pretrained("project-themis/Themis-RM-14B", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload Qwen3ForSequenceClassification
Browse files- config.json +1 -1
- model-00001-of-00012.safetensors +1 -1
- model-00002-of-00012.safetensors +1 -1
- model-00003-of-00012.safetensors +1 -1
- model-00004-of-00012.safetensors +1 -1
- model-00005-of-00012.safetensors +1 -1
- model-00006-of-00012.safetensors +1 -1
- model-00007-of-00012.safetensors +1 -1
- model-00008-of-00012.safetensors +1 -1
- model-00009-of-00012.safetensors +1 -1
- model-00010-of-00012.safetensors +1 -1
- model-00011-of-00012.safetensors +1 -1
- model-00012-of-00012.safetensors +1 -1
config.json
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"rope_theta": 1000000,
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"transformers_version": "4.57.
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"rope_theta": 1000000,
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