File size: 2,483 Bytes
c8f92de 93b32d3 c8f92de 94c9945 c8f92de a26120f 94c9945 93b32d3 94c9945 a26120f 94c9945 b0b7f18 94c9945 c8f92de |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 |
# /// script
# requires-python = ">=3.12"
# dependencies = [
# "torch",
# "torchvision",
# "transformers",
# "accelerate",
# "peft",
# "slack-sdk",
# ]
# ///
try:
# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3-Coder-30B-A3B-Instruct")
model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-Coder-30B-A3B-Instruct")
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('Qwen_Qwen3-Coder-30B-A3B-Instruct_1.txt', 'w', encoding='utf-8') as f:
f.write('Everything was good in Qwen_Qwen3-Coder-30B-A3B-Instruct_1.txt')
except Exception as e:
import os
from slack_sdk import WebClient
client = WebClient(token=os.environ['SLACK_TOKEN'])
client.chat_postMessage(
channel='#exp-slack-alerts',
text='Problem in <https://huggingface.co/datasets/model-metadata/code_execution_files/blob/main/Qwen_Qwen3-Coder-30B-A3B-Instruct_1.txt|Qwen_Qwen3-Coder-30B-A3B-Instruct_1.txt>',
)
with open('Qwen_Qwen3-Coder-30B-A3B-Instruct_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("Qwen/Qwen3-Coder-30B-A3B-Instruct")
model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-Coder-30B-A3B-Instruct")
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='Qwen_Qwen3-Coder-30B-A3B-Instruct_1.txt',
repo_id='model-metadata/code_execution_files',
path_in_repo='Qwen_Qwen3-Coder-30B-A3B-Instruct_1.txt',
repo_type='dataset',
)
|