Instructions to use ArthurZ/Ilama-3.2-1B with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ArthurZ/Ilama-3.2-1B with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="ArthurZ/Ilama-3.2-1B", trust_remote_code=True)# Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("ArthurZ/Ilama-3.2-1B", trust_remote_code=True) model = AutoModel.from_pretrained("ArthurZ/Ilama-3.2-1B", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
Update modeling_ilama.py
Browse files- modeling_ilama.py +1 -1
modeling_ilama.py
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@@ -4,5 +4,5 @@ from .configuration_ilama import IlamaConfig
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class IlamaModel(LlamaModel):
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config_class = IlamaConfig
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class IlamaForCausalLM(LlamaForCausalLM)
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config_class = IlamaConfig
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class IlamaModel(LlamaModel):
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config_class = IlamaConfig
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class IlamaForCausalLM(LlamaForCausalLM):
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config_class = IlamaConfig
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