Instructions to use Ngit/open-buddy-70b-v10.1-train-4bits-lima with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Ngit/open-buddy-70b-v10.1-train-4bits-lima with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("OpenBuddy/openbuddy-llama2-70b-v10.1-bf16") model = PeftModel.from_pretrained(base_model, "Ngit/open-buddy-70b-v10.1-train-4bits-lima") - Notebooks
- Google Colab
- Kaggle
Update handler.py
Browse files- handler.py +1 -1
handler.py
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@@ -29,7 +29,7 @@ class EndpointHandler:
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self.tokenizer = AutoTokenizer.from_pretrained(path)
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print("Memory footprint: ", self.model.get_memory_footprint())
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print("Device map: ", model.hf_device_map)
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def __call__(self, data: Any) -> List[List[Dict[str, str]]]:
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self.tokenizer = AutoTokenizer.from_pretrained(path)
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print("Memory footprint: ", self.model.get_memory_footprint())
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print("Device map: ", self.model.hf_device_map)
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def __call__(self, data: Any) -> List[List[Dict[str, str]]]:
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