Instructions to use hassan7272/tinyllama-lora-eval with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use hassan7272/tinyllama-lora-eval with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("TinyLlama/TinyLlama-1.1B-Chat-v1.0") model = PeftModel.from_pretrained(base_model, "hassan7272/tinyllama-lora-eval") - Transformers
How to use hassan7272/tinyllama-lora-eval with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("hassan7272/tinyllama-lora-eval", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.model from hassan7272/tinyllama-lora-eval: direct link, hf CLI and curl.
- Browser
- Download file 500 kB
-
https://huggingface.co/hassan7272/tinyllama-lora-eval/resolve/main/tokenizer.model
- Command line
-
hf download hf://hassan7272/tinyllama-lora-eval/tokenizer.model
-
curl -L -o tokenizer.model https://huggingface.co/hassan7272/tinyllama-lora-eval/resolve/main/tokenizer.model
500 kB
- Xet hash:
- 409b63d0f14ab5da7909ddcb93f85878ef0e4f19bfa91194b68ac5b45a5b6e87
- Size of remote file:
- 500 kB
- SHA256:
- 9e556afd44213b6bd1be2b850ebbbd98f5481437a8021afaf58ee7fb1818d347
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