Create README.md

README.md

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+---
+pipeline_tag: text-generation
+inference: true
+widget:
+- text: 'Hello!'
+  example_title: Hello world
+  group: Python
+library_name: transformers
+---
+
+This model is randomly initialized, using the config from [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) but with smaller size. 
+**Note the model is in bfloat16**.
+
+Codes:
+```python
+import transformers
+import torch
+import os
+from huggingface_hub import create_repo, upload_folder
+
+source_model_id = 'meta-llama/Meta-Llama-3-8B-Instruct'
+save_path = '/tmp/yujiepan/meta-llama-3-tiny-random'
+repo_id = 'yujiepan/meta-llama-3-tiny-random'
+
+config = transformers.AutoConfig.from_pretrained(
+    source_model_id,
+    trust_remote_code=True,
+)
+config._name_or_path = source_model_id
+config.hidden_size = 4
+config.intermediate_size = 14
+config.num_attention_heads = 2
+config.num_key_value_heads = 1
+config.num_hidden_layers = 2
+config.torch_dtype = "bfloat16"
+
+model = transformers.AutoModelForCausalLM.from_config(
+    config,
+    trust_remote_code=True,
+)
+model = model.to(torch.bfloat16)
+model.save_pretrained(save_path)
+
+tokenizer = transformers.AutoTokenizer.from_pretrained(
+    source_model_id,
+    trust_remote_code=True,
+)
+tokenizer.save_pretrained(save_path)
+
+model.float().generate(torch.tensor([[1, 2, 3]]).long(), max_length=16)
+
+os.system(f'ls -alh {save_path}')
+create_repo(repo_id, exist_ok=True)
+upload_folder(repo_id=repo_id, folder_path=save_path)
+```