LLM
Collection
Collection of OpenVINO optimized LLMs
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135 items
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Updated
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17
The provided OpenVINO™ IR model is compatible with:
pip install optimum[openvino]
from transformers import AutoTokenizer
from optimum.intel.openvino import OVModelForCausalLM
model_id = "OpenVINO/gemma-2-9b-it-fp16-ov"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = OVModelForCausalLM.from_pretrained(model_id)
inputs = tokenizer("What is OpenVINO?", return_tensors="pt")
outputs = model.generate(**inputs, max_length=200)
text = tokenizer.batch_decode(outputs)[0]
print(text)
For more examples and possible optimizations, refer to the OpenVINO Large Language Model Inference Guide.
pip install openvino-genai huggingface_hub
import huggingface_hub as hf_hub
model_id = "OpenVINO/gemma-2-9b-it-fp16-ov"
model_path = "gemma-2-9b-it-fp16-ov"
hf_hub.snapshot_download(model_id, local_dir=model_path)
import openvino_genai as ov_genai
device = "CPU"
pipe = ov_genai.LLMPipeline(model_path, device)
print(pipe.generate("What is OpenVINO?", max_length=200))
More GenAI usage examples can be found in OpenVINO GenAI library docs and samples
Check the original model card for original model card for limitations.
The original model is distributed under gemma license. More details can be found in original model card.
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