Instructions to use EdBerg/continue01_arabic_trained_model_mistral7b_completion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use EdBerg/continue01_arabic_trained_model_mistral7b_completion with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/mistral-7b-v0.3-bnb-4bit") model = PeftModel.from_pretrained(base_model, "EdBerg/continue01_arabic_trained_model_mistral7b_completion") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
|
Download README.md from EdBerg/continue01_arabic_trained_model_mistral7b_completion: direct link, hf CLI and curl.
- Browser
- Download file 1.3 kB
-
https://huggingface.co/EdBerg/continue01_arabic_trained_model_mistral7b_completion/resolve/main/README.md
- Command line
-
hf download hf://EdBerg/continue01_arabic_trained_model_mistral7b_completion/README.md
-
curl -L -o README.md https://huggingface.co/EdBerg/continue01_arabic_trained_model_mistral7b_completion/resolve/main/README.md
1.3 kB
metadata
library_name: peft
license: apache-2.0
base_model: unsloth/mistral-7b-v0.3-bnb-4bit
tags:
- unsloth
- generated_from_trainer
model-index:
- name: continue01_arabic_trained_model_mistral7b_completion
results: []
continue01_arabic_trained_model_mistral7b_completion
This model is a fine-tuned version of unsloth/mistral-7b-v0.3-bnb-4bit 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: 5e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 80
Training results
Framework versions
- PEFT 0.14.0
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1