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llm001 L04 Full: 190M, 20-step test

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README.md ADDED
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+ ---
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+ base_model: cmz1024/olmo3-190m-zh-full
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+ license: apache-2.0
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+ language:
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+ - zh
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+ tags:
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+ - llm001
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+ - olmo3
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+ - chinese
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+ - pretrained
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+ ---
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+
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+ # OLMo3-190M-zh-full
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+
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+ 为零基础 AI 大模型研发训练营(llm001)L04 Full 模型(190M 参数,20 步测试训练)。
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+
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+ ## 模型配置
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+
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+ - hidden_size: 768, num_layers: 12, num_heads: 12, intermediate_size: 3072
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+ - vocab_size: 48000, sliding_window: 4096
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+
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+ ## 训练配置
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+
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+ - 数据:cmz1024/llm101-olmo3-zh-demo-data (500M tokens)
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+ - 训练:H100, max_steps=20, bs=16×8=128, lr=5e-4, bf16
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+
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+ ## 用法
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+
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+ ```python
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+ model = AutoModelForCausalLM.from_pretrained("cmz1024/olmo3-190m-zh-full")
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+ tok = AutoTokenizer.from_pretrained("cmz1024/olmo3-190m-zh-full")
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+ ```
config.json ADDED
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+ {
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+ "architectures": [
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+ "Olmo3ForCausalLM"
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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": 2,
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+ "dtype": "float32",
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+ "eos_token_id": 0,
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+ "hidden_act": "silu",
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+ "hidden_size": 768,
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "layer_types": [
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+ "sliding_attention",
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+ "sliding_attention",
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+ "sliding_attention",
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+ "full_attention",
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+ "sliding_attention",
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+ "sliding_attention",
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+ "sliding_attention",
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+ "full_attention",
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+ "sliding_attention",
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+ "sliding_attention",
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+ "sliding_attention",
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+ "full_attention"
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+ ],
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+ "max_position_embeddings": 4096,
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+ "model_type": "olmo3",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "num_key_value_heads": 12,
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+ "pad_token_id": 1,
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+ "rms_norm_eps": 1e-06,
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+ "rope_parameters": {
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+ "rope_theta": 500000,
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+ "rope_type": "default"
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+ },
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+ "sliding_window": 4096,
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+ "tie_word_embeddings": false,
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+ "transformers_version": "5.7.0",
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+ "use_cache": false,
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+ "vocab_size": 48000
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+ }
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+ "pad_token_id": 1,
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+ "transformers_version": "5.7.0",
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+ "use_cache": true
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+ }
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tokenizer.json ADDED
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tokenizer_config.json ADDED
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+ {
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+ "backend": "tokenizers",
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+ "bos_token": "<|bos|>",
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+ "eos_token": "<|endoftext|>",
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+ "is_local": true,
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+ "pad_token": "<|pad|>",
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+ "tokenizer_class": "TokenizersBackend",
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+ "unk_token": "<|unk|>"
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+ }
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