Instructions to use MakTek/code_llama-5e-new_data with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use MakTek/code_llama-5e-new_data with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("NousResearch/CodeLlama-7b-hf") model = PeftModel.from_pretrained(base_model, "MakTek/code_llama-5e-new_data") - Notebooks
- Google Colab
- Kaggle
results_code_llama-5e-0.1_new_data
This model is a fine-tuned version of NousResearch/CodeLlama-7b-hf on an unknown 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: 0.0002
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 5
Training results
Framework versions
- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Downloads last month
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Base model
NousResearch/CodeLlama-7b-hf