aws / aws/amazon-sagemaker-examples
[Bug Report] Pretrained Llama 2 Model URI leads to a .tar.gz with dummy.txt file
- Dominant language
- Jupyter Notebook
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Description
**Link to the notebook**
Add the link to the notebook.
N/A
**Describe the bug**
A clear and concise description of what the bug is.
I get the error: `not a gzip file` when I run the following code:
```
model_id, model_version = (
"meta-textgeneration-llama-2-7b-f",
"1.2.0",
)
scope = "inference"
model_uri = model_uris.retrieve(
model_id=model_id,
model_version=model_version,
model_scope=scope,
)
print(f"model_url: {model_uri}\n")
script_uri = script_uris.retrieve(
model_id=model_id,
model_version=model_version,
script_scope=scope,
)
print(f"script_uri: {script_uri}\n")
instance_type = instance_types.retrieve_default(
model_id=model_id, model_version=model_version, scope=scope
)
print(f"instance_type: {instance_type}\n")
image_uri = image_uris.retrieve(
region=None,
framework=None,
image_scope=scope,
model_id=model_id,
model_version=model_version,
instance_type=instance_type,
)
print(f"image_uri: {image_uri}\n")
model = Model(
image_uri=image_uri,
model_data=model_uri,
source_dir=script_uri,
entry_point="inference.py",
role=role,
name="some-model-name",
predictor_cls=Predictor,
)
health_check_timeout = 300
predictor = model.deploy(
initial_instance_count=1,
instance_type=instance_type,
endpoint_name="some-endpoint-name",
)
```
After inspecting the model uri on s3 https://s3.console.aws.amazon.com/s3/object/jumpstart-cache-prod-us-east-1?region=us-east-1&prefix=meta-infer%2Finfer-meta-textgeneration-llama-2-7b-f.tar.gz I noticed that it only contains a dummy.txt file.
**To reproduce**
A clear, step-by-step set of instructions to reproduce the bug.
**Logs**
If applicable, add logs to help explain your problem.
You may also attach an `.ipynb` file to this issue if it includes relevant logs or output.
Contributor guide
Research direction
Start by reproducing the notebook code using model_uris.retrieve for meta-textgeneration-llama-2-7b version 1.2.0, then inspect the returned S3 archive and the Model deployment path. Done means the URI contains the intended pretrained model rather than only dummy.txt, and deployment no longer fails with “not a gzip file”.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- aws, jupyter-notebook, python
- Domain
- cloud, machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 25/100