Text Classification
Transformers
Safetensors
English
qwen3
code
reward-model
multilingual
text-embeddings-inference
Instructions to use project-themis/Themis-RM-1.7B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use project-themis/Themis-RM-1.7B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="project-themis/Themis-RM-1.7B")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("project-themis/Themis-RM-1.7B") model = AutoModelForSequenceClassification.from_pretrained("project-themis/Themis-RM-1.7B") - Notebooks
- Google Colab
- Kaggle
Update README.md
Browse files
README.md
CHANGED
|
@@ -18,7 +18,7 @@ language:
|
|
| 18 |
|
| 19 |
# Themis-RM-1.7B
|
| 20 |
|
| 21 |
-
[](https://huggingface.co/collections/project-themis/themis-reward-model-collection)
|
| 23 |
[](https://huggingface.co/collections/project-themis/themis-preference-datasets-and-benchmarks)
|
| 24 |
[](https://github.com/iNeil77/Themis)
|
|
@@ -244,7 +244,7 @@ This model is released under the [Apache 2.0 License](https://www.apache.org/lic
|
|
| 244 |
@article{themis2025,
|
| 245 |
title={Themis: Training Robust Multilingual Code Reward Models for Flexible Multi-Criteria Scoring},
|
| 246 |
author={},
|
| 247 |
-
journal={arXiv preprint arXiv:
|
| 248 |
year={2025}
|
| 249 |
}
|
| 250 |
-
```
|
|
|
|
| 18 |
|
| 19 |
# Themis-RM-1.7B
|
| 20 |
|
| 21 |
+
[](https://arxiv.org/abs/2605.00754)
|
| 22 |
[](https://huggingface.co/collections/project-themis/themis-reward-model-collection)
|
| 23 |
[](https://huggingface.co/collections/project-themis/themis-preference-datasets-and-benchmarks)
|
| 24 |
[](https://github.com/iNeil77/Themis)
|
|
|
|
| 244 |
@article{themis2025,
|
| 245 |
title={Themis: Training Robust Multilingual Code Reward Models for Flexible Multi-Criteria Scoring},
|
| 246 |
author={},
|
| 247 |
+
journal={arXiv preprint arXiv:2605.00754},
|
| 248 |
year={2025}
|
| 249 |
}
|
| 250 |
+
```
|