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.gitattributes CHANGED
@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
 
 
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  *.zip filter=lfs diff=lfs merge=lfs -text
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  *.zst filter=lfs diff=lfs merge=lfs -text
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  *tfevents* filter=lfs diff=lfs merge=lfs -text
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+ tokenizer.json filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,71 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ library_name: transformers
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+ pipeline_tag: text-generation
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+ inference: true
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+ widget:
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+ - text: Hello!
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+ example_title: Hello world
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+ group: Python
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+ ---
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+
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+ This tiny model is for debugging. It is randomly initialized with the config adapted from [THUDM/GLM-4-32B-0414](https://huggingface.co/THUDM/GLM-4-32B-0414).
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+
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+ ### Example usage:
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+
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+ ```python
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+ from transformers import pipeline
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+ model_id = "tiny-random/glm-4"
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+ pipe = pipeline(
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+ "text-generation", model=model_id, device="cuda",
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+ trust_remote_code=True, max_new_tokens=20,
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+ )
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+ print(pipe("Hello World!"))
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+ ```
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+
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+ ### Codes to create this repo:
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+
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+ ```python
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+ import torch
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+
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+ from transformers import (
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+ AutoConfig,
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+ AutoModelForCausalLM,
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+ AutoTokenizer,
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+ GenerationConfig,
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+ pipeline,
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+ set_seed,
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+ )
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+
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+ source_model_id = "THUDM/GLM-4-32B-0414"
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+ save_folder = "/tmp/tiny-random/glm-4"
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+
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+ tokenizer = AutoTokenizer.from_pretrained(
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+ source_model_id, trust_remote_code=True,
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+ )
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+ tokenizer.save_pretrained(save_folder)
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+
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+ config = AutoConfig.from_pretrained(
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+ source_model_id, trust_remote_code=True,
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+ )
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+ config.hidden_size = 16
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+ config.head_dim = 16
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+ config.intermediate_size = 32
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+ config.num_attention_heads = 1
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+ config.num_hidden_layers = 2
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+ config.num_key_value_heads = 1
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+ config.tie_word_embeddings = False
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+ model = AutoModelForCausalLM.from_config(
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+ config,
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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.generation_config = GenerationConfig.from_pretrained(
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+ source_model_id, trust_remote_code=True,
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+ )
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+ set_seed(42)
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+ with torch.no_grad():
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+ for name, p in sorted(model.named_parameters()):
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+ torch.nn.init.normal_(p, 0, 0.5)
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+ print(name, p.shape)
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+ model.save_pretrained(save_folder)
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+ ```
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+ # 可用工具
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+
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+
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+ <|assistant|>
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+ {{ content }}
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+ {%- elif role == 'assistant' and meta %}
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+ <|assistant|>{{ meta }}
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+ {{ content }}
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+ {%- elif role == 'observation' %}
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+ <|observation|>
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+ {{ content }}
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+ {%- endif %}
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+ {%- endfor %}
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+ {% if add_generation_prompt %}<|assistant|>{% endif %}
config.json ADDED
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+ {
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+ "architectures": [
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+ "Glm4ForCausalLM"
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+ "attention_bias": false,
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+ "torch_dtype": "bfloat16",
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+ "transformers_version": "4.52.0.dev0",
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+ "use_cache": true,
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+ "vocab_size": 151552
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+ }
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