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RichardErkhov/andrijdavid_-_tinyllama-dare-awq
andrijdavid_-_tinyllama-dare-awq is a machine learning model from RichardErkhov. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Downloads · 30 days
17
41% of all-time downloads
All-time downloads
41
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766 MB on disk
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.safetensors766 MB · 99%
How the weights are stored.
I32969M · 88%
From the Hugging Face model README
Quantization made by Richard Erkhov.
tinyllama-dare - AWQ
language:
The following models were included in the merge:
The users of this model (hereinafter referred to as "the Model") should be aware of the following points prior to using the Model:
Factual Inaccuracy: The Model has been trained on a diverse set of data sources. However, it may occasionally generate outputs that contain factual inaccuracies. Users are advised to verify the factual correctness of the information provided by the Model, especially when using it for critical applications.
Potential Biases: Despite efforts to ensure fairness and neutrality, the Model may still exhibit biases inherent in the training data. These biases do not reflect the views or intentions of the developers. Users should be cautious of these potential biases, especially when using the Model in contexts where fairness and impartiality are crucial.
Hallucination: The Model might generate content that is not grounded in reality, commonly referred to as "hallucinations." This is a known limitation of language models and should be considered when interpreting the Model's outputs.
Inappropriate Content: While measures have been taken to minimize the risk, the Model might still generate content that could be deemed offensive, inappropriate, or not suitable for all audiences. We advise users to exercise discretion and consider the context of use.
By using the Model, users acknowledge and agree to the terms stated in this disclaimer. This disclaimer is subject to change without notice, and the latest version can be found on the Model's Hugging Face page.
Detailed results can be found here
| Metric | Value |
|---|---|
| Avg. | 38.64 |
| AI2 Reasoning Challenge (25-Shot) | 37.29 |
| HellaSwag (10-Shot) | 62.78 |
| MMLU (5-Shot) | 25.20 |
| TruthfulQA (0-shot) | 39.01 |
| Winogrande (5-shot) | 65.90 |
| GSM8k (5-shot) | 1.67 |