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
Download tokenizer.model from Erland/tinyllama-test-merged-16bit: direct link, hf CLI and curl.
- Browser
- Download file 500 kB
-
https://huggingface.co/Erland/tinyllama-test-merged-16bit/resolve/main/tokenizer.model
- Command line
-
hf download hf://Erland/tinyllama-test-merged-16bit/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/Erland/tinyllama-test-merged-16bit/resolve/main/tokenizer.model
500 kB
- Xet hash:
- 409b63d0f14ab5da7909ddcb93f85878ef0e4f19bfa91194b68ac5b45a5b6e87
- Size of remote file:
- 500 kB
- SHA256:
- 9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
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