# If the endpoint is already deployed, you can directly connect to it
co.sagemaker_finetuning.connect_to_endpoint(endpoint_name=endpoint_name)

message = "Classify the following text as either very negative, negative, neutral, positive or very positive: mr. deeds is , as comedy goes , very silly -- and in the best way."
result = co.sagemaker_finetuning.chat(message=message)
print(result)
```

You can also evaluate your finetuned model using an evaluation dataset. The following is an example with the [ScienceQA](https://scienceqa.github.io/) evaluation using these [data](https://github.com/cohere-ai/cohere-developer-experience/blob/main/notebooks/data/scienceQA_eval.jsonl):

```Python PYTHON
import json
from tqdm import tqdm

eval_data_path = "<path_to_scienceQA_eval.jsonl>"

total = 0
correct = 0
for line in tqdm(open(eval_data_path).readlines()):
    total += 1
    question_answer_json = json.loads(line)
    question = question_answer_json["messages"][0]["content"]
    answer = question_answer_json["messages"][1]["content"]
    model_ans = co.sagemaker_finetuning.chat(message=question, temperature=0).text
    if model_ans == answer:
        correct += 1

print(f"Accuracy of finetuned model is %.3f" % (correct / total))
```

## Step 8. Delete the endpoint (optional)

After you successfully performed the inference, you can delete the deployed endpoint to avoid being charged continuously.

```Python PYTHON
co.sagemaker_finetuning.delete_endpoint()
co.sagemaker_finetuning.close()
```

## Step 9. Unsubscribe to the listing (optional)

If you would like to unsubscribe to the model package, follow these steps. Before you cancel the subscription, ensure that you do not have any [deployable models](https://console.aws.amazon.com/sagemaker/home#/models) created from the model package or using the algorithm.

**Note:** You can find this information by looking at the container name associated with the model.

Here's how you do that:

* Navigate to **Machine Learning** tab on the [Your Software subscriptions](https://aws.amazon.com/marketplace/ai/library?productType=ml\&ref_=mlmp_gitdemo_indust) page;
* Locate the listing that you want to cancel the subscription for, and then choose **Cancel Subscription** to cancel the subscription.