初始化项目，由ModelHub XC社区提供模型
Model: kehanlu/llama-3.2-8B-Instruct Source: Original Platform
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README.md
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README.md
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---
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library_name: transformers
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tags: []
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---
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This repository contains the text-only LLM portion of `meta-llama/Llama-3.2-11B-Vision-Instruct`
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**How it was done**
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```python
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from collections import OrderedDict
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from transformers import MllamaForConditionalGeneration, AutoModelForCausalLM
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from transformers.models.mllama.modeling_mllama import MllamaCrossAttentionDecoderLayer
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llama32_id = "meta-llama/Llama-3.2-11B-Vision-Instruct"
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llama32 = MllamaForConditionalGeneration.from_pretrained(
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llama32_id,
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torch_dtype=torch.bfloat16,
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device_map="cuda:0",
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)
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new_layers = []
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for idx, layer in enumerate(llama32.language_model.model.layers):
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if isinstance(layer, MllamaCrossAttentionDecoderLayer):
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# CrossAttention layers are only take effect when image is provided.
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# Ignore here since we want text-only model
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pass
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else:
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new_layers.append(layer)
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llama32.language_model.model.cross_attention_layers = []
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llama32.language_model.model.layers = torch.nn.ModuleList(new_layers)
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# Now llama32.language_model is identical to Llama3.1-8B-Instruct, except the embedding size(+8)
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# see: https://github.com/huggingface/transformers/blob/a22a4378d97d06b7a1d9abad6e0086d30fdea199/src/transformers/models/mllama/modeling_mllama.py#L1667C9-L1667C26
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new_llama32_state_dict = OrderedDict()
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for k, v in llama32.language_model.state_dict().items():
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if k == "model.embed_tokens.weight":
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v = v[:128256, :]
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new_llama32_state_dict[k] = v
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# Load a llama31 for the architecture
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llama31_id = "meta-llama/Llama-3.1-8B-Instruct"
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llama31 = AutoModelForCausalLM.from_pretrained(
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llama31_id,
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torch_dtype=torch.bfloat16,
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device_map="cuda:1",
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)
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llama31.load_state_dict(new_llama32_state_dict)
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# <All keys matched successfully>
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llama31.save_pretrained("./my-cool-llama3.2")
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```
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**Note:**
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In the original tokenizer, there are `date_string` in `tokenizer.chat_template` (which append the current date when calling `tokenizer.apply_chat_template(messages)`).
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I removed this behavior in this repo. Please be aware when you use `AutoTokenizer.from_pretrained(this_repo)`.
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config.json
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config.json
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{
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"_name_or_path": "/home/khlu/lab/tmp/llama32",
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"architectures": [
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"LlamaForCausalLM"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"bos_token_id": 128000,
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"eos_token_id": [
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128001,
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128008,
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128009
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],
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 4096,
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"initializer_range": 0.02,
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"intermediate_size": 14336,
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"max_position_embeddings": 131072,
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"mlp_bias": false,
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"model_type": "llama",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": {
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"factor": 8.0,
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"high_freq_factor": 4.0,
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"low_freq_factor": 1.0,
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"original_max_position_embeddings": 8192,
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"rope_type": "llama3"
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},
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"rope_theta": 500000.0,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.46.1",
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"use_cache": true,
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"vocab_size": 128256
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}
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generation_config.json
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"temperature": 0.6,
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"top_p": 0.9,
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"transformers_version": "4.46.1"
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}
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23
special_tokens_map.json
Normal file
23
special_tokens_map.json
Normal file
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|
||||
"pad_token": {
|
||||
"content": "<|finetune_right_pad_id|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false
|
||||
}
|
||||
}
|
||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:9816d43bd5347d64bccc66b7710947fb18e9818cc660215b1462061d4a44e449
|
||||
size 17210088
|
||||
2071
tokenizer_config.json
Normal file
2071
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user