Feature Extraction
Transformers
Safetensors
English
llama
text-generation-inference
unsloth
text-embeddings-inference
Instructions to use Erland/tinyllama-test-merged-16bit with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Erland/tinyllama-test-merged-16bit with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="Erland/tinyllama-test-merged-16bit")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("Erland/tinyllama-test-merged-16bit") model = AutoModel.from_pretrained("Erland/tinyllama-test-merged-16bit", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Desktop
Uploaded finetuned model
- Developed by: Erland
- License: apache-2.0
- Finetuned from model : unsloth/tinyllama-bnb-4bit
This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.
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Model tree for Erland/tinyllama-test-merged-16bit
Base model
unsloth/tinyllama-bnb-4bit