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YAML Metadata Warning: The pipeline tag "conversational" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, text2text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, any-to-any, other

Another EXL2 version of AlpinDale's https://huggingface.co/alpindale/goliath-120b this one being at 2.37BPW.

2.64BPW

Pippa llama2 Chat was used as the calibration dataset.

Can be run on two RTX 3090s w/ 24GB vram each.

Assuming Windows overhead, the following figures should be more or less close enough for estimation of your own use.

2.37BPW @ 4096 ctx
    empty ctx
        GPU split: 16/24
        GPU1: 17.4/24GB
        GPU2: 19.5/24GB
        11~ tk/s
     3000+ ctx
      8~-12 tk/s

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