Instructions to use iisys-hof/OLaPhLLM_v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use iisys-hof/OLaPhLLM_v2 with Transformers:
# Use a pipeline as a high-level helper # Warning: Pipeline type "translation" is no longer supported in transformers v5. # You must load the model directly (see below) or downgrade to v4.x with: # pip install "transformers<5.0.0" from transformers import pipeline pipe = pipeline("translation", model="iisys-hof/OLaPhLLM_v2")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("iisys-hof/OLaPhLLM_v2") model = AutoModelForCausalLM.from_pretrained("iisys-hof/OLaPhLLM_v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download tokenizer.json from iisys-hof/OLaPhLLM_v2: direct link, hf CLI and curl.
- Browser
- Download file 34.4 MB
-
https://huggingface.co/iisys-hof/OLaPhLLM_v2/resolve/main/tokenizer.json
- Command line
-
hf download hf://iisys-hof/OLaPhLLM_v2/tokenizer.json
-
curl -L -o tokenizer.json https://huggingface.co/iisys-hof/OLaPhLLM_v2/resolve/main/tokenizer.json
34.4 MB
- Xet hash:
- 8a1c972efe40230fe1f344de6dd80db9ea5b016ffe1b833b4263ab06c4ea9294
- Size of remote file:
- 34.4 MB
- SHA256:
- a09888eecfc2c471e752492bac14515a6f6e0af75dac67698f274234538a9b20
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