Instructions to use IntellectusAI/zephyr_beta with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use IntellectusAI/zephyr_beta with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("TheBloke/zephyr-7B-alpha-GPTQ") model = PeftModel.from_pretrained(base_model, "IntellectusAI/zephyr_beta") - Notebooks
- Google Colab
- Kaggle
| license: mit | |
| library_name: peft | |
| tags: | |
| - trl | |
| - sft | |
| - generated_from_trainer | |
| base_model: TheBloke/zephyr-7B-alpha-GPTQ | |
| model-index: | |
| - name: zephyr_beta | |
| results: [] | |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You | |
| should probably proofread and complete it, then remove this comment. --> | |
| [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/praxisbusiness/huggingface/runs/v89nj10m) | |
| [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/praxisbusiness/huggingface/runs/v89nj10m) | |
| # zephyr_beta | |
| This model is a fine-tuned version of [TheBloke/zephyr-7B-alpha-GPTQ](https://huggingface.co/TheBloke/zephyr-7B-alpha-GPTQ) on the None 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: 8 | |
| - eval_batch_size: 8 | |
| - seed: 42 | |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 | |
| - lr_scheduler_type: cosine | |
| - training_steps: 200 | |
| - mixed_precision_training: Native AMP | |
| ### Training results | |
| ### Framework versions | |
| - PEFT 0.11.2.dev0 | |
| - Transformers 4.42.0.dev0 | |
| - Pytorch 2.3.0+cu121 | |
| - Datasets 2.19.1 | |
| - Tokenizers 0.19.1 |