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license: apache-2.0
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# GreenBit LLaMA
This is GreenBitAI's pretrained **2-bit** TinyLLaMA model with extreme compression yet still strong performance.
Please refer to our [Github page](https://github.com/GreenBitAI/low_bit_llama) for the code to run the model and more information.
## Model Description
- **Developed by:** [GreenBitAI](https://github.com/GreenBitAI)
- **Model type:** Causal (Llama 2)
- **Language(s) (NLP):** English
- **License:** [Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0), [Llama 2 license agreement](https://ai.meta.com/resources/models-and-libraries/llama-downloads/)
## Zero-Shot Evaluation
| Task | Metric | TinyLLaMA 1.1B q2g32 | TinyLLaMA 1.1B q2g8 | LLaMA 3B q2g32 | LLaMA 3B q2g16 | LLaMA 3B q2g8 | LLaMA-1 7B q2g32 | LLaMA-2 7B q2g32 | LLaMA-2 7B q2g8 | LLaMA 1.1B FP16 | LLaMA 3B FP16 | LLaMA-1 7B FP16 |
|---------------|----------|----------------------|---------------------|----------------|----------------|---------------|------------------|------------------|----------------|----------------|-----------------|-----------------|
| Openbookqa | acc | 0.152 | 0.192 | 0.196 | 0.238 | 0.242 | 0.224 | 0.246 | 0.296 | 0.208 | 0.27 | 0.29 |
| | ac_norm | 0.328 | 0.338 | 0.332 | 0.358 | 0.362 | 0.388 | 0.376 | 0.4 | 0.368 | 0.4 | 0.41 |
| arc_challenge | acc | 0.3268 | 0.2278 | 0.279 | 0.2978 | 0.3148 | 0.3422 | 0.3268 | 0.3618 | 0.243 | 0.34 | 0.39 |
| | ac_norm | 0.3387 | 0.273 | 0.2944 | 0.3319 | 0.3345 | 0.3387 | 0.3387 | 0.372 | 0.288 | 0.37 | 0.41 |
| hellawswag | acc | 0.34 | 0.3769 | 0.4238 | 0.444 | 0.462 | 0.4996 | 0.4961 | 0.5379 | 0.403 | 0.49 | 0.68 |
| | ac_norm | 0.4097 | 0.4711 | 0.5685 | 0.5988 | 0.6242 | 0.6447 | 0.6464 | 0.7014 | 0.503 | 0.67 | 0.73 |
| piqa | acc | 0.6518 | 0.6931 | 0.7024 | 0.716 | 0.7291 | 0.7476 | 0.7503 | 0.7715 | 0.71 | 0.75 | 0.78 |
| | ac_norm | 0.6393 | 0.6812 | 0.7116 | 0.7247 | 0.7312 | 0.7443 | 0.7421 | 0.7568 | 0.688 | 0.76 | 0.78 |
| arc_easy | acc | 0.4411 | 0.5109 | 0.5997 | 0.646 | 0.6528 | 0.6061 | 0.6174 | 0.6254 | 0.533 | 0.69 | 0.68 |
| | ac_norm | 0.3716 | 0.412 | 0.5417 | 0.58 | 0.5972 | 0.4566 | 0.4781 | 0.4958 | 0.43 | 0.65 | 0.52 |
| Winogrande | acc | 0.532 | 0.5249 | 0.5683 | 0.5888 | 0.6054 | 0.6283 | 0.6298 | 0.6582 | 0.558 | 0.62 | 0.68 |
| boolq | acc | 0.592 | 0.6174 | 0.6281 | 0.6636 | 0.6327 | 0.6425 | 0.7061 | 0.7242 | 0.583 | 0.68 | 0.75 |
| truthfulqa_mc | mc1 | 0.2338 | 0.2277 | 0.2509 | 0.2118 | 0.2252 | 0.224 | 0.2313 | 0.2399 | 0.228 | 0.22 | 0.21 |
| | mc2 | 0.4211 | 0.406 | 0.3962 | 0.3501 | 0.3625 | 0.3702 | 0.3854 | 0.3795 | 0.401 | 0.35 | 0.34 |
| anli_r1 | acc | 0.363 | 0.336 | 0.337 | 0.334 | 0.344 | 0.331 | 0.333 | 0.363 | 0.354 | 0.33 | 0.35 |
| anli_r2 | acc | 0.331 | 0.346 | 0.335 | 0.332 | 0.331 | 0.326 | 0.349 | 0.347 | 0.341 | 0.32 | 0.34 |
| anli_r3 | acc | 0.3758 | 0.3633 | 0.3358 | 0.3383 | 0.3425 | 0.3417 | 0.36 | 0.3733 | 0.358 | 0.35 | 0.37 |
| wic | acc | 0.5 | 0.5 | 0.4984 | 0.5094 | 0.4969 | 0.4984 | 0.4953 | 0.489 | 0.5 | 0.48 | 0.5 |
| rte | acc | 0.4874 | 0.4874 | 0.5596 | 0.5993 | 0.5632 | 0.639 | 0.6065 | 0.6426 | 0.516 | 0.58 | 0.56 |
| record | f1 | 0.7608 | 0.8023 | 0.8502 | 0.8625 | 0.8687 | 0.8859 | 0.8872 | 0.9037 | 0.82 | 0.88 | 0.91 |
| | em | 0.753 | 0.7934 | 0.8427 | 0.8545 | 0.8612 | 0.8781 | 0.8801 | 0.8959 | 0.818 | 0.89 | 0.91 |
| Average | | 0.438 | 0.4498 | 0.4881 | 0.5037 | 0.5087 | 0.5122 | 0.5181 | 0.5391 | 0.469 | 0.528 | 0.5519 |
| model size | GiB | 0.5 | 0.6 | 1.2 | 1.3 | 1.5 | 2.2 | 2.2 | 2.9 | 4.4 | 6.8 | 12.5 | |