| | --- |
| | library_name: transformers |
| | pipeline_tag: text-generation |
| | inference: true |
| | widget: |
| | - text: Hello! |
| | example_title: Hello world |
| | group: Python |
| | --- |
| | |
| | This model is for debugging purposes. 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 a 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-codestral-v0.1-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!")) |
| | |
| | with open(__file__, 'r') as f: |
| | codes = f.read() |
| | with open(f'{save_path}/README.md', 'w') as f: |
| | f.write( |
| | f'''--- |
| | library_name: transformers |
| | pipeline_tag: text-generation |
| | inference: true |
| | widget: |
| | - text: Hello! |
| | example_title: Hello world |
| | group: Python |
| | --- |
| | |
| | This model is for debugging purposes. It is randomly initialized using the config from [{model_id}](https://huggingface.co/{model_id}) but with a smaller size. |
| | |
| | Codes: |
| | ```python |
| | {codes} |
| | ```''' |
| | ) |
| | |
| | create_repo(repo_id, exist_ok=True) |
| | upload_folder(repo_id=repo_id, folder_path=save_path, repo_type='model') |
| | |
| | ``` |