Open-Source AI Meetup

pip install logfire-callback

export LOGFIRE_TOKEN=your_logfire_token

from transformers import Trainer, TrainingArguments
from logfire_callback import LogfireCallback

# Initialize your model, dataset, etc.

training_args = TrainingArguments(
    output_dir="./results",
    num_train_epochs=3,
    # ... other training arguments
)

trainer = Trainer(
    model=model,
    args=training_args,
    train_dataset=train_dataset,
    callbacks=[LogfireCallback()]  # Add the Logfire callback here
)

trainer.train()

from tqdm import tqdm
import time

reasoning_data = []

for example in tqdm(ds, desc="answering"):
    try:
        response = client.chat.completions.create(
            model='deepseek-reasoner',  # Using DeepSeek-R1 for reasoning
            messages=[
                {"role": "system", "content": example['system_prompt']},
                {"role": "user", "content": example['question']},
            ],
            stream=False,
            max_tokens=4096,
            temperature=0.7,
        )
        
        answer = response.choices[0].message.content
        reasoning = response.choices[0].message.reasoning_content

        reasonng_example = {
            "id": example['id'],
            "question": example['question'],
            'answer': answer,
            'reasoning': reasoning,
        }

        reasoning_data.append(reasonng_example)
    except Exception as e:
        print(f"Error translating example: {e}")
        time.sleep(3)  # Wait for 3 seconds before continuing
        continue  # Skip the current example and move to the next one