Snowflake has only released the inference code - meaning the code you need to "run" the model. So if you take the weights they have released (which is the model that is a result of training), you can host the weights and inference code, and feed prompts to it, to get answers. But you don't have the actual source code you need to produce the weights in the first place.

As an example of what open source actually means for LLMs, you can look at what AI2 does with their OLMo model (https://allenai.org/olmo), where each model that they release comes with:

> Full training data used for these models, including code that produces the training data, from AI2’s Dolma, and WIMBD for analyzing pretraining data.

> Full model weights, training code, training logs, training metrics in the form of Weights & Biases logs, and inference code.

> 500+ checkpoints per model, from every 1000 steps during the training process, available as revisions on HuggingFace.

> Evaluation code under the umbrella of AI2’s Catwalk and Paloma.

> Fine-tuning code and adapted models (with Open Instruct)

> All code, weights, and intermediate checkpoints are released under the Apache 2.0 License.

OLMo is what "truly open" is, while the rest is openwashing and marketing.