Implement Jina CLIP v2 and NewBie dual CLIP (#11415)
* Implement Jina CLIP v2 * Support quantized Gemma in NewBie dual CLIP
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4
nodes.py
4
nodes.py
@@ -970,7 +970,7 @@ class DualCLIPLoader:
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def INPUT_TYPES(s):
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return {"required": { "clip_name1": (folder_paths.get_filename_list("text_encoders"), ),
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"clip_name2": (folder_paths.get_filename_list("text_encoders"), ),
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"type": (["sdxl", "sd3", "flux", "hunyuan_video", "hidream", "hunyuan_image", "hunyuan_video_15", "kandinsky5", "kandinsky5_image"], ),
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"type": (["sdxl", "sd3", "flux", "hunyuan_video", "hidream", "hunyuan_image", "hunyuan_video_15", "kandinsky5", "kandinsky5_image", "newbie"], ),
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},
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"optional": {
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"device": (["default", "cpu"], {"advanced": True}),
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@@ -980,7 +980,7 @@ class DualCLIPLoader:
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CATEGORY = "advanced/loaders"
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DESCRIPTION = "[Recipes]\n\nsdxl: clip-l, clip-g\nsd3: clip-l, clip-g / clip-l, t5 / clip-g, t5\nflux: clip-l, t5\nhidream: at least one of t5 or llama, recommended t5 and llama\nhunyuan_image: qwen2.5vl 7b and byt5 small"
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DESCRIPTION = "[Recipes]\n\nsdxl: clip-l, clip-g\nsd3: clip-l, clip-g / clip-l, t5 / clip-g, t5\nflux: clip-l, t5\nhidream: at least one of t5 or llama, recommended t5 and llama\nhunyuan_image: qwen2.5vl 7b and byt5 small\nnewbie: gemma-3-4b-it, jina clip v2"
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def load_clip(self, clip_name1, clip_name2, type, device="default"):
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clip_type = getattr(comfy.sd.CLIPType, type.upper(), comfy.sd.CLIPType.STABLE_DIFFUSION)
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