Instructions to use JakeOh/LLaDA-Tiny with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use JakeOh/LLaDA-Tiny with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="JakeOh/LLaDA-Tiny", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("JakeOh/LLaDA-Tiny", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
| {{ bos_token }} | |
| {%- for message in messages %} | |
| {%- if (message['role'] == 'system') -%} | |
| {{'<|system|>' + '\n' + message['content'].strip() + '<|end|>' + '\n'}} | |
| {%- elif (message['role'] == 'user') -%} | |
| {{'<|user|>' + '\n' + message['content'].strip() + '<|end|>' + '\n' + '<|assistant|>' + '\n'}} | |
| {%- elif message['role'] == 'assistant' -%} | |
| {{message['content'].strip() + '<|end|>' + '\n'}} | |
| {%- endif %} | |
| {%- endfor %} | |