--- tags: - merge license: other model-index: - name: QuartetAnemoi-70B-t0.0001 results: - task: type: text-generation name: Text Generation dataset: name: AI2 Reasoning Challenge (25-Shot) type: ai2_arc config: ARC-Challenge split: test args: num_few_shot: 25 metrics: - type: acc_norm value: 73.38 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=alchemonaut/QuartetAnemoi-70B-t0.0001 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: HellaSwag (10-Shot) type: hellaswag split: validation args: num_few_shot: 10 metrics: - type: acc_norm value: 88.9 name: normalized accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=alchemonaut/QuartetAnemoi-70B-t0.0001 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: MMLU (5-Shot) type: cais/mmlu config: all split: test args: num_few_shot: 5 metrics: - type: acc value: 75.42 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=alchemonaut/QuartetAnemoi-70B-t0.0001 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: TruthfulQA (0-shot) type: truthful_qa config: multiple_choice split: validation args: num_few_shot: 0 metrics: - type: mc2 value: 69.53 source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=alchemonaut/QuartetAnemoi-70B-t0.0001 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: Winogrande (5-shot) type: winogrande config: winogrande_xl split: validation args: num_few_shot: 5 metrics: - type: acc value: 85.32 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=alchemonaut/QuartetAnemoi-70B-t0.0001 name: Open LLM Leaderboard - task: type: text-generation name: Text Generation dataset: name: GSM8k (5-shot) type: gsm8k config: main split: test args: num_few_shot: 5 metrics: - type: acc value: 68.61 name: accuracy source: url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=alchemonaut/QuartetAnemoi-70B-t0.0001 name: Open LLM Leaderboard --- # QuartetAnemoi-70B-t0.0001 A sequential merge using a custom algorithm (NearSwap) of: - [152334H/miqu-1-70b-sf](https://huggingface.co/152334H/miqu-1-70b-sf) - [Sao10K/WinterGoddess-1.4x-70B-L2](https://huggingface.co/Sao10K/WinterGoddess-1.4x-70B-L2) - [Aurora-Nights-70B-v1.0](https://huggingface.co/sophosympatheia/Aurora-Nights-70B-v1.0) - [Xwin-LM-70B-V0.1](https://huggingface.co/Xwin-LM/Xwin-LM-70B-V0.1)
In our testing, this model seems like a storyteller, as might be expected, but the changes from this merge are extremely soft. We were impressed that, unlike most models, at the end of a story it did not often use cliches such as "In the end", "And so", "beacon of hope", etc.

# Quants Most of the popular quant formats are available now, thanks to community efforts. | Type | Misc | Author | | ----- | ----- | ----- | | [GGUF](https://huggingface.co/alchemonaut/QuartetAnemoi-70B-t0.0001-GGUF/tree/main) | | alchemonaut | | [GGUF](https://huggingface.co/Nexesenex/alchemonaut_QuartetAnemoi-70B-iMat.GGUF) | iMat | Nexesenex | | [GGUF](https://huggingface.co/mradermacher/QuartetAnemoi-70B-t0.0001-i1-GGUF) | iMat | mradermacher | | [GGUF](https://huggingface.co/mradermacher/QuartetAnemoi-70B-t0.0001-GGUF) | Full Set | mradermacher | | [exl2](https://huggingface.co/llmixer/QuartetAnemoi-70B-t0.0001-2.5bpw-h6-exl2) | 2.5bpw | llmixer | | [exl2](https://huggingface.co/altomek/QuartetAnemoi-70B-t0.0001-3.75bpw-EXL2) | 3.75bpw | altomek | | [exl2](https://huggingface.co/llmixer/QuartetAnemoi-70B-t0.0001-4bpw-h6-exl2) | 4.0bpw| llmixer | | [exl2](https://huggingface.co/alchemonaut/QuartetAnemoi-70B-t0.0001-b4.6-h8-exl2) | 4.6bpw| alchemonaut | | [exl2](https://huggingface.co/llmixer/QuartetAnemoi-70B-t0.0001-6.0bpw-h6-exl2) | 6.0bpw | llmixer | | [AWQ](https://huggingface.co/tachyphylaxis/QuartetAnemoi-70B-t0.0001-AWQ) | | tachyphylaxis |

# NearSwap Algorithm NearSwap retains most of the weights of the base model (Miqu), but when a weight is similar between the two, it is interpolated to the secondary model value. A parameter *t* specifies the sameness threshold. When the distance between two values is below *t*, the weight from the secondary model is used. This version of the model uses *t* = 0.0001. At this *t*, about 0.8% of weights are fully switched to the secondary model during each pass. Model quality rapidly degrades above *t* = 0.0025: - *t* = 0.0001 (~0.8% full swap): This model - *t* = 0.0003 (~2% full swap) - *t* = 0.001 (~10% full swap): [BoreanGale-70B](https://huggingface.co/alchemonaut/BoreanGale-70B) - *t* = 0.0025 (~18% full swap): Generates one paragraph okay, but then reverts to garbage - *t* = 0.005 (~35% full swap): Garbage; semi-related word lists - *t* = 0.01 (~55% full swap): Garbage; pseudorandom tokens output For QuartetAnemoi-70B-t0.0001, the three secondary models were each merged sequentially with *t* = 0.0001. NearSwap implementation: ``` t: Union[float, np.ndarray], v0: Union[np.ndarray, torch.Tensor], v1: Union[np.ndarray, torch.Tensor], ... lweight = numpy.absolute(v0-v1) lweight = t / lweight lweight = numpy.nan_to_num(lweight, nan=1.0, posinf=1.0, neginf=1.0) numpy.clip(lweight, a_min=0.0, a_max=1.0, out=lweight) res = lerp(lweight,v0,v1) ```

# License and Use Since the ultimate origin of Miqu is at this time unknown beyond speculation, this model is for noncommercial research use only.

# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard) Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_alchemonaut__QuartetAnemoi-70B-t0.0001) | Metric |Value| |---------------------------------|----:| |Avg. |76.86| |AI2 Reasoning Challenge (25-Shot)|73.38| |HellaSwag (10-Shot) |88.9| |MMLU (5-Shot) |75.42| |TruthfulQA (0-shot) |69.53| |Winogrande (5-shot) |85.32| |GSM8k (5-shot) |68.61|