Instructions to use priamai/mistral-7b-bnb-4bit-cyber-ner with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use priamai/mistral-7b-bnb-4bit-cyber-ner with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("priamai/mistral-7b-bnb-4bit-cyber-ner", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Uploaded model
- Developed by: priamai
- License: apache-2.0
- Finetuned from model : unsloth/mistral-7b-bnb-4bit
This mistral model was trained 2x faster with Unsloth and Huggingface's TRL library.
Num GPUs = 1
Num Epochs = 2
Batch size per device = 2
Gradient Accumulation steps = 2
Total batch size = 8
otal steps = 2
Number of trainable parameters = 41,943,040
Total Samples = 800
Source of reports: ORKL
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Model tree for priamai/mistral-7b-bnb-4bit-cyber-ner
Base model
unsloth/mistral-7b-bnb-4bit