pe-nlp / R1-Qwen2.5-32B-Instruct-code

huggingface.co
Total runs: 40
24-hour runs: 0
7-day runs: 0
30-day runs: 0
Model's Last Updated: January 29 2025
text-generation

Introduction of R1-Qwen2.5-32B-Instruct-code

Model Details of R1-Qwen2.5-32B-Instruct-code

original

This model is a fine-tuned version of Qwen/Qwen2.5-32B-Instruct on the Sky-T1 dataset.

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure
Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 2e-05
  • train_batch_size: 1
  • eval_batch_size: 8
  • seed: 42
  • distributed_type: multi-GPU
  • num_devices: 8
  • gradient_accumulation_steps: 12
  • total_train_batch_size: 96
  • total_eval_batch_size: 64
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: cosine
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 2.0
Training results
Framework versions
  • Transformers 4.46.1
  • Pytorch 2.4.0a0+f70bd71a48.nv24.06
  • Datasets 3.1.0
  • Tokenizers 0.20.3

Runs of pe-nlp R1-Qwen2.5-32B-Instruct-code on huggingface.co

40
Total runs
0
24-hour runs
0
3-day runs
0
7-day runs
0
30-day runs

More Information About R1-Qwen2.5-32B-Instruct-code huggingface.co Model

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R1-Qwen2.5-32B-Instruct-code huggingface.co is an AI model on huggingface.co that provides R1-Qwen2.5-32B-Instruct-code's model effect (), which can be used instantly with this pe-nlp R1-Qwen2.5-32B-Instruct-code model. huggingface.co supports a free trial of the R1-Qwen2.5-32B-Instruct-code model, and also provides paid use of the R1-Qwen2.5-32B-Instruct-code. Support call R1-Qwen2.5-32B-Instruct-code model through api, including Node.js, Python, http.

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pe-nlp R1-Qwen2.5-32B-Instruct-code online free

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R1-Qwen2.5-32B-Instruct-code install

R1-Qwen2.5-32B-Instruct-code is an open source model from GitHub that offers a free installation service, and any user can find R1-Qwen2.5-32B-Instruct-code on GitHub to install. At the same time, huggingface.co provides the effect of R1-Qwen2.5-32B-Instruct-code install, users can directly use R1-Qwen2.5-32B-Instruct-code installed effect in huggingface.co for debugging and trial. It also supports api for free installation.

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