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# /// script
# requires-python = ">=3.12"
# dependencies = [
# "torch",
# "torchvision",
# "transformers",
# "diffusers",
# "sentence-transformers",
# "accelerate",
# "peft",
# "slack-sdk",
# ]
# ///
try:
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("MiniMaxAI/MiniMax-M2")
model = AutoModelForCausalLM.from_pretrained("MiniMaxAI/MiniMax-M2")
messages = [
{"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
messages,
add_generation_prompt=True,
tokenize=True,
return_dict=True,
return_tensors="pt",
).to(model.device)
outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))
with open('MiniMaxAI_MiniMax-M2_1.txt', 'w', encoding='utf-8') as f:
f.write('Everything was good in MiniMaxAI_MiniMax-M2_1.txt')
except Exception as e:
import os
from slack_sdk import WebClient
client = WebClient(token=os.environ['SLACK_TOKEN'])
client.chat_postMessage(
channel='#hub-model-metadata-snippets-sprint',
text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/MiniMaxAI_MiniMax-M2_1.txt|MiniMaxAI_MiniMax-M2_1.txt>',
)
with open('MiniMaxAI_MiniMax-M2_1.txt', 'a', encoding='utf-8') as f:
import traceback
f.write('''```CODE:
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("MiniMaxAI/MiniMax-M2")
model = AutoModelForCausalLM.from_pretrained("MiniMaxAI/MiniMax-M2")
messages = [
{"role": "user", "content": "Who are you?"},
]
inputs = tokenizer.apply_chat_template(
messages,
add_generation_prompt=True,
tokenize=True,
return_dict=True,
return_tensors="pt",
).to(model.device)
outputs = model.generate(**inputs, max_new_tokens=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))
```
ERROR:
''')
traceback.print_exc(file=f)
finally:
from huggingface_hub import upload_file
upload_file(
path_or_fileobj='MiniMaxAI_MiniMax-M2_1.txt',
repo_id='model-metadata/code_execution_files',
path_in_repo='MiniMaxAI_MiniMax-M2_1.txt',
repo_type='dataset',
)
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