Token Classification
Transformers
Safetensors
qwen2
Generated from Trainer
trl
prm
text-generation-inference
Instructions to use plaguss/Qwen2.5-Math-7B-PRM-0.1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use plaguss/Qwen2.5-Math-7B-PRM-0.1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="plaguss/Qwen2.5-Math-7B-PRM-0.1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("plaguss/Qwen2.5-Math-7B-PRM-0.1") model = AutoModelForTokenClassification.from_pretrained("plaguss/Qwen2.5-Math-7B-PRM-0.1", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Model save
Browse files- all_results.json +8 -0
- eval_results.json +8 -0
all_results.json
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{
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"epoch": 0.999671592775041,
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"eval_accuracy": 0.9262595253307568,
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"eval_loss": 0.2609236240386963,
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"eval_runtime": 59.1825,
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"eval_samples_per_second": 173.126,
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"eval_steps_per_second": 5.424
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}
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eval_results.json
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{
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"epoch": 0.999671592775041,
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"eval_accuracy": 0.9262595253307568,
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"eval_loss": 0.2609236240386963,
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"eval_runtime": 59.1825,
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"eval_samples_per_second": 173.126,
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"eval_steps_per_second": 5.424
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}
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