Update README.md
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README.md
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@@ -52,7 +52,7 @@ pip install -U llama-index-embeddings-huggingface
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from llama_index.embeddings.huggingface import HuggingFaceEmbedding
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model = HuggingFaceEmbedding(
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model_name="llamaindex/vdr-2b-v1",
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device="cpu", # "mps" for mac, "cuda" for nvidia GPUs
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trust_remote_code=True,
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)
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@@ -81,7 +81,7 @@ min_pixels = 1 * 28 * 28
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# Load the embedding model and processor
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model = Qwen2VLForConditionalGeneration.from_pretrained(
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'llamaindex/vdr-2b-v1',
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# These are the recommended kwargs for the model, but change them as needed
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attn_implementation="flash_attention_2",
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torch_dtype=torch.bfloat16,
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@@ -89,7 +89,7 @@ model = Qwen2VLForConditionalGeneration.from_pretrained(
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).eval()
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processor = AutoProcessor.from_pretrained(
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'llamaindex/vdr-2b-v1',
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min_pixels=min_pixels,
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max_pixels=max_pixels
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)
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@@ -217,7 +217,7 @@ via SentenceTransformers
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from sentence_transformers import SentenceTransformer
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model = SentenceTransformer(
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model_name_or_path="llamaindex/vdr-2b-v1",
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device="cuda",
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trust_remote_code=True,
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# These are the recommended kwargs for the model, but change them as needed if you don't have CUDA
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from llama_index.embeddings.huggingface import HuggingFaceEmbedding
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model = HuggingFaceEmbedding(
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model_name="llamaindex/vdr-2b-multi-v1",
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device="cpu", # "mps" for mac, "cuda" for nvidia GPUs
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trust_remote_code=True,
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)
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# Load the embedding model and processor
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model = Qwen2VLForConditionalGeneration.from_pretrained(
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'llamaindex/vdr-2b-multi-v1',
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# These are the recommended kwargs for the model, but change them as needed
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attn_implementation="flash_attention_2",
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torch_dtype=torch.bfloat16,
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).eval()
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processor = AutoProcessor.from_pretrained(
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'llamaindex/vdr-2b-multi-v1',
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min_pixels=min_pixels,
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max_pixels=max_pixels
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)
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from sentence_transformers import SentenceTransformer
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model = SentenceTransformer(
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model_name_or_path="llamaindex/vdr-2b-multi-v1",
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device="cuda",
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trust_remote_code=True,
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# These are the recommended kwargs for the model, but change them as needed if you don't have CUDA
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