fix apex
Browse files- README.md +6 -8
- vision_tower_builder.py +8 -3
README.md
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@@ -20,10 +20,9 @@ We introduce <strong>Kangaroo</strong>, a powerful Multimodal Large Language Mod
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</li>
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</ol>
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-
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## Quick Start
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###
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See our [github page](https://github.com/KangarooGroup/Kangaroo)
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### Multi-round Chat with 🤗 Transformers
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@@ -31,21 +30,20 @@ See our [github page](https://github.com/KangarooGroup/Kangaroo)
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import torch
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from transformers import AutoTokenizer, AutoModelForCausalLM
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tokenizer = AutoTokenizer.from_pretrained(
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model = AutoModelForCausalLM.from_pretrained(
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torch_dtype=torch.bfloat16,
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trust_remote_code=True,
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)
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model = model.to("cuda")
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terminators = [tokenizer.eos_token_id, tokenizer.convert_tokens_to_ids("<|eot_id|>")]
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# replace /path/to/video to your own path to the video
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video_path = "/path/to/video"
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# Round 1
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query = "
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out, history = model.chat(video_path=video_path,
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query=query,
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tokenizer=tokenizer,
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@@ -57,7 +55,7 @@ out, history = model.chat(video_path=video_path,
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print('Assitant: \n', out)
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# Round 2
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query = "
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out, history = model.chat(video_path=video_path,
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query=query,
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tokenizer=tokenizer,
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</li>
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</ol>
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## Quick Start
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### Prepare Model and Environment
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See our [github page](https://github.com/KangarooGroup/Kangaroo)
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### Multi-round Chat with 🤗 Transformers
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import torch
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from transformers import AutoTokenizer, AutoModelForCausalLM
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model_path = "/path/to/kangaroo"
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tokenizer = AutoTokenizer.from_pretrained(model_path)
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model = AutoModelForCausalLM.from_pretrained(
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model_path,
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torch_dtype=torch.bfloat16,
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trust_remote_code=True,
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)
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model = model.to("cuda")
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terminators = [tokenizer.eos_token_id, tokenizer.convert_tokens_to_ids("<|eot_id|>")]
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video_path = "/path/to/video"
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# Round 1
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query = "Give a brief description of the video."
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out, history = model.chat(video_path=video_path,
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query=query,
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tokenizer=tokenizer,
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print('Assitant: \n', out)
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# Round 2
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query = "What happend at the end of the video?"
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out, history = model.chat(video_path=video_path,
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query=query,
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tokenizer=tokenizer,
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vision_tower_builder.py
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@@ -686,7 +686,7 @@ class CLIPVisionCfg:
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timm_proj_bias: bool = False # enable bias final projection
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eva_model_name: str = "eva-clip-l-14-448" # a valid eva model name overrides layers, width, patch_size
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qkv_bias: bool = True
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fusedLN: bool =
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xattn: bool = True
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postnorm: bool = False
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rope: bool = True
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@@ -707,8 +707,13 @@ def build_vision_tower(precision: str = 'bf16'):
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if vision_cfg.fusedLN:
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else:
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norm_layer = partial(LayerNorm, eps=1e-6)
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timm_proj_bias: bool = False # enable bias final projection
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eva_model_name: str = "eva-clip-l-14-448" # a valid eva model name overrides layers, width, patch_size
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qkv_bias: bool = True
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fusedLN: bool = True
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xattn: bool = True
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postnorm: bool = False
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rope: bool = True
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if vision_cfg.fusedLN:
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try:
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from apex.normalization import FusedLayerNorm
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norm_layer = partial(FusedLayerNorm, eps=1e-6)
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except:
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print("")
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norm_layer = partial(LayerNorm, eps=1e-6)
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else:
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norm_layer = partial(LayerNorm, eps=1e-6)
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