Upload folder using huggingface_hub

README.md

@@ -0,0 +1,82 @@
+---
+library_name: transformers
+pipeline_tag: text-generation
+inference: true
+widget:
+- text: Hello!
+  example_title: Hello world
+  group: Python
+---
+
+This model is for debugging. It is randomly initialized using the config from [mistralai/Mamba-Codestral-7B-v0.1](https://huggingface.co/mistralai/Mamba-Codestral-7B-v0.1) but with smaller size. 
+
+Codes:
+```python
+import os
+
+import torch
+
+from huggingface_hub import create_repo, upload_folder
+from transformers import (
+    AutoModelForCausalLM,
+    AutoTokenizer,
+    GenerationConfig,
+    Mamba2Config,
+    pipeline,
+    set_seed,
+)
+
+model_id = "mistralai/Mamba-Codestral-7B-v0.1"
+repo_id = "yujiepan/mamba2-tiny-random"
+save_path = f"/tmp/{repo_id}"
+
+os.system(f'rm -rf {save_path}')
+
+config = Mamba2Config.from_pretrained(model_id)
+config.use_cache = True
+config.num_hidden_layers = 2
+config.num_heads = 8
+config.head_dim = 4
+config.hidden_size = 8
+config.expand = 4
+config.intermediate_size = 32
+config.state_size = 8
+config.n_groups = 2
+
+assert config.intermediate_size == \
+    config.hidden_size * config.expand == config.num_heads * config.head_dim
+assert config.num_heads // config.n_groups > 0
+assert config.num_heads % 8 == 0
+
+tokenizer = AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
+tokenizer.save_pretrained(save_path)
+
+model = AutoModelForCausalLM.from_config(
+    config, torch_dtype=torch.bfloat16,
+    trust_remote_code=True,
+)
+model.generation_config = GenerationConfig.from_pretrained(
+    model_id,
+    trust_remote_code=True,
+)
+
+set_seed(42)
+with torch.no_grad():
+    for name, p in sorted(model.named_parameters()):
+        print(name, p.shape)
+        torch.nn.init.uniform_(p, -0.5, 0.5)
+
+model.save_pretrained(save_path)
+
+pipe = pipeline(
+    "text-generation",
+    model=save_path,
+    device="cuda",
+    trust_remote_code=True,
+    max_new_tokens=20,
+)
+print(pipe("Hello World!"))
+
+create_repo(repo_id, exist_ok=True)
+upload_folder(repo_id=repo_id, folder_path=save_path, repo_type='model')
+```