sagnikM/ppo_sgd_qwen3_1.7b_1e-2
sagnikM/ppo_sgd_qwen3_1.7b_1e-2 is a 2 billion parameter language model based on the Qwen3 architecture. This model is shared on Hugging Face Hub, with a context length of 40960 tokens. Further details regarding its specific training, capabilities, and intended use cases are currently marked as 'More Information Needed' in its model card.
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Model Overview
This model, sagnikM/ppo_sgd_qwen3_1.7b_1e-2, is a 2 billion parameter language model built upon the Qwen3 architecture. It is hosted on the Hugging Face Hub, indicating its availability for use within the transformers ecosystem. The model boasts a substantial context length of 40960 tokens, which is a notable feature for processing longer sequences of text.
Key Characteristics
- Architecture: Qwen3-based model.
- Parameters: 2 billion parameters.
- Context Length: Supports a context window of 40960 tokens.
- Availability: Shared on the Hugging Face Hub.
Current Information Limitations
As per its model card, specific details regarding the model's developer, funding, precise model type, language(s) of training, license, and finetuning origins are currently marked as "More Information Needed." Similarly, comprehensive information on its direct and downstream uses, potential biases, risks, limitations, training data, training procedure, and evaluation results are not yet provided. Users are advised to consult future updates to the model card for these critical details.