BigWeave Viable
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All viable models from the BigWeave series, excluding quantized versions
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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, audio-text-to-text, 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
BigWeave v9 90B
The BigWeave models aim to identify merge settings equaling or surpassing the performance of Goliath-120b. The version number merely tracks various attempts and is not a quality indicator. Only results demonstrating good performance are retained and shared.
This version is a DARE-TIES merge of two passthrough merges: Xwin-LM-70b-v0.1 + Euryale-1.3-70b (BigWeave v6) and Platypus2-70b-instruct + WinterGoddess-1.4x-70b (BigWeave v8). Both models individually show strong performance, and the merged model achieves even lower perplexity than each model separately.
The 90b size allows for 4bit quants to fit into 48GB of VRAM.
Prompting Format
Vicuna and Alpaca.
Merge process
The models used in the merge are Xwin-LM-70b-v0.1, Euryale-1.3-70b, Platypus2-70b-instruct and WinterGoddess-1.4x-70b.
Merge configuration: ``` slices: - sources: - model: Xwin-LM/Xwin-LM-70B-V0.1 layer_range: [0,12] - sources: - model: Sao10K/Euryale-1.3-L2-70B layer_range: [9,14] - sources: - model: Xwin-LM/Xwin-LM-70B-V0.1 layer_range: [12,62] - sources: - model: Sao10K/Euryale-1.3-L2-70B layer_range: [54,71] - sources: - model: Xwin-LM/Xwin-LM-70B-V0.1 layer_range: [62,80] merge_method: passthrough dtype: float16
slices: - sources: - model: garage-bAInd/Platypus2-70B-instruct layer_range: [0,12] - sources: - model: Sao10K/WinterGoddess-1.4x-70B-L2 layer_range: [9,14] - sources: - model: garage-bAInd/Platypus2-70B-instruct layer_range: [12,62] - sources: - model: Sao10/WinterGoddess-1.4x-70B-L2 layer_range: [54,71] - sources: - model: garage-bAInd/Platypus2-70B-instruct layer_range: [62,80] merge_method: passthrough dtype: float16
models: - model: llmixer/BigWeave-v8-90b parameters: weight: 0.5 density: 0.5 merge_method: dare_ties base_model: llmixer/BigWeave-v6-90b dtype: float16
# Acknowledgements
[@Xwin-LM](https://huggingface.co/Xwin-LM) For creating Xwin
[@Sao10K](https://huggingface.co/Sao10K) For creating Euryale and WinterGoddess
[@garage-bAInd](https://huggingface.co/garage-bAInd) For creating Platypus2
[@alpindale](https://huggingface.co/alpindale) For creating the original Goliath
[@chargoddard](https://huggingface.co/chargoddard) For developing [mergekit](https://github.com/cg123/mergekit).
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