Update README.md

README.md

@@ -1,182 +1,13 @@
 ---
+license: llama2
+language:
+- en
+pipeline_tag: conversational
 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
+- 2.5bpw
+- h6
+- exl2
 ---
+Exllamav2 2.5bpw h6 quant for [alchemonaut/QuartetAnemoi-70B-t0.0001](https://huggingface.co/alchemonaut/QuartetAnemoi-70B-t0.0001).
 
-<img src=https://huggingface.co/alchemonaut/QuartetAnemoi-70B-t0.0001/resolve/main/anemoi.png>
-
-# 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)
-
-<br/>
-
-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.
-
-<br/>
-
-Quants available at: [alchemonaut/QuartetAnemoi-70B-t0.0001-GGUF](https://huggingface.co/alchemonaut/QuartetAnemoi-70B-t0.0001-GGUF/tree/main)
-
-<br/>
-<br/>
-
-# 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)
-```
-<br/>
-<br/>
-
-
-# License and Use
-
-Since the ultimate origin of Miqu is at this time unknown beyond speculation, this model is for noncommercial research use only.
-
-<br/>
-<br/>
-
-
-# [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|
-
+Default calibration dataset.