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", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Upload Qwen3ForSequenceClassification
Browse files- config.json +32 -2
- model-00001-of-00002.safetensors +1 -1
- model-00002-of-00002.safetensors +1 -1
- model.safetensors.index.json +1 -0
config.json
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"attention_bias": false,
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"attention_dropout": 0.0,
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"eos_token_id": 151645,
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"head_dim": 128,
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"hidden_act": "silu",
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"label2id": {
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"max_position_embeddings": 40960,
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"max_window_layers": 28,
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"model_type": "qwen3",
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"rope_theta": 1000000,
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"sliding_window": null,
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"tie_word_embeddings": true,
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"transformers_version": "4.51.0",
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"unsloth_fixed": true,
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"use_cache": false,
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"use_sliding_window": false,
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"attention_bias": false,
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"attention_dropout": 0.0,
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"dtype": "float32",
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"eos_token_id": 151645,
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"head_dim": 128,
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"hidden_act": "silu",
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"label2id": {
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"LABEL_0": 0
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"layer_types": [
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],
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"max_position_embeddings": 40960,
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"max_window_layers": 28,
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"model_type": "qwen3",
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"rope_theta": 1000000,
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"sliding_window": null,
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"tie_word_embeddings": true,
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"transformers_version": "4.57.1",
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"unsloth_fixed": true,
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"use_cache": false,
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"use_sliding_window": false,
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model-00001-of-00002.safetensors
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size 4969539560
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size 4969539560
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model-00002-of-00002.safetensors
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size 1912803968
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model.safetensors.index.json
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{
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"metadata": {
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"total_size": 6882308096
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"weight_map": {
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{
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"metadata": {
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"total_parameters": 1720577024,
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"total_size": 6882308096
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"weight_map": {
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