--- license: afl-3.0 library_name: transformers tags: - UNA - juanako --- # For a better performance check out our v2 at [fblgit/UNA-ThePitbull-21.4B-v2](https://huggingface.co/fblgit/UNA-ThePitbull-21.4B-v2) # UNA-ThePitbull 21.4B v1 Introducing the best LLM in the industry. Nearly as good as a 70B, just a 21.4B based on saltlux/luxia-21.4b-alignment-v1.0 ![UNA - ThePitbull 21.4B v1](https://huggingface.co/fblgit/UNA-ThePitbull-21.4-v1/resolve/main/UNA-ThePitbull.png) This model has not been poisoned to score high and be useless. We release him becaues its the real deal of EQ & IQ all together in a crazy powerful smart and conversational model. So far the #1 of them at 25/5/2024 Quant version available at [bartowski/UNA-ThePitbull-21.4-v1-GGUF](https://huggingface.co/bartowski/UNA-ThePitbull-21.4-v1-GGUF) # For a better performance check out our v2 at [fblgit/UNA-ThePitbull-21.4B-v2](https://huggingface.co/fblgit/UNA-ThePitbull-21.4B-v2) # Evaluations Can only be compared with its non-una base model: the original luxia-21.4b. ## UNA (VLLM) Evaluations ``` | Tasks |Version| Filter |n-shot| Metric |Value | |Stderr| |--------------|------:|----------------|-----:|-----------|-----:|---|-----:| |gsm8k | 3|strict-match | 5|exact_match|0.7566|± |0.0118| | | |flexible-extract| 5|exact_match|0.7582|± |0.0118| |hellaswag | 1|none | 10|acc |0.8168|± |0.0039| | | |none | 10|acc_norm |0.9188|± |0.0027| |winogrande | 1|none | 5|acc |0.8635|± |0.0097| |mmlu | N/A|none | 0|acc |0.6444|± |0.0038| |arc_challenge | 1|none | 25|acc |0.7747|± |0.0122| | | |none | 25|acc_norm |0.7850|± |0.0120| |truthfulqa_mc2| 2|none | 0|acc |0.7902|± |0.0134| |mathqa | 1|none | 0|acc |0.4030|± | 0.009| | | |none | 0|acc_norm |0.4034|± | 0.009| |pubmedqa | 1|none | 0|acc |0.6860|± |0.0208| |boolq | 2|none | 0|acc |0.8401|± |0.0064| ``` ## Original (VLLM) Evaluations ``` | Tasks |Version| Filter |n-shot| Metric |Value | |Stderr| |--------------|------:|----------------|-----:|-----------|-----:|---|-----:| |gsm8k | 3|strict-match | 5|exact_match|0.7528|± |0.0119| | | |flexible-extract| 5|exact_match|0.7521|± |0.0119| |hellaswag | 1|none | 10|acc |0.8117|± |0.0039| | | |none | 10|acc_norm |0.9167|± |0.0028| |winogrande | 1|none | 5|acc |0.8682|± |0.0095| |mmlu | N/A|none | 0|acc |0.6448|± |0.0038| |arc_challenge | 1|none | 25|acc |0.7688|± |0.0123| | | |none | 25|acc_norm |0.7730|± |0.0122| |truthfulqa_mc2| 2|none | 0|acc |0.7895|± |0.0133| |mathqa | 1|none | 0|acc |0.4000|± | 0.009| | | |none | 0|acc_norm |0.4003|± | 0.009| |pubmedqa | 1|none | 0|acc |0.6680|± |0.0211| |boolq | 2|none | 0|acc |0.8346|± |0.0065| ``` ## UNA Details Only MLP were Uniformed leaving room for further optimisations. You should be able to perform a SFT+DPO again on this model at moderate speeds. 1e-4/2e-5/etc.