Update README.md

README.md

@@ -162,163 +162,6 @@ For GGUFs, [mradermacher/Lamarck-14B-v0.3-i1-GGUF](https://huggingface.co/mrader
 
 - **[sometimesanotion/lamarck-14b-prose-model_stock](https://huggingface.co/sometimesanotion/lamarck-14b-prose-model_stock)** - This brings in a little influence from [EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2](https://huggingface.co/EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2), [oxyapi/oxy-1-small](https://huggingface.co/oxyapi/oxy-1-small), and [allura-org/TQ2.5-14B-Sugarquill-v1](https://huggingface.co/allura-org/TQ2.5-14B-Sugarquill-v1).
 
-**Note on abliteration:**  This author believes that adjacent services and not language models themselves are where guardrails are best placed.  Effort to de-censor Lamarck will resume after the model has been further studied.
-
-### Configuration
-
-The following YAML configuration was used to produce this model:
-
-```yaml
-name:                lamarck-14b-reason-della                  # This contributes the knowledge and reasoning pool, later to be merged
-merge_method:        della                                     # with the dominant instruction-following model
-base_model:          arcee-ai/Virtuoso-Small
-tokenizer_source:    arcee-ai/Virtuoso-Small
-parameters:
-  int8_mask:         false
-  normalize:         true
-  rescale:           false
-  density:           0.30
-  weight:            0.50
-  epsilon:           0.08
-  lambda:            1.00
-models:
-  - model:           CultriX/SeQwence-14B-EvolMerge
-    parameters:
-      density:       0.70
-      weight:        0.90
-  - model:           sometimesanotion/lamarck-14b-reason-model_stock
-    parameters:
-      density:       0.90
-      weight:        0.60
-  - model:           CultriX/Qwen2.5-14B-Wernicke
-    parameters:
-      density:       0.20
-      weight:        0.30
-dtype:               bfloat16
-out_dtype:           bfloat16
----
-name:                lamarck-14b-prose-della                  # This contributes the prose, later to be merged
-merge_method:        della                                    # with the dominant instruction-following model
-base_model:          arcee-ai/Virtuoso-Small
-tokenizer_source:    arcee-ai/Virtuoso-Small
-parameters:
-  int8_mask:         false
-  normalize:         true
-  rescale:           false
-  density:           0.30
-  weight:            0.50
-  epsilon:           0.08
-  lambda:            0.95
-models:
-  - model:           sthenno-com/miscii-14b-1028
-    parameters:
-      density:       0.40
-      weight:        0.90
-  - model:           sometimesanotion/lamarck-14b-prose-model_stock
-    parameters:
-      density:       0.60
-      weight:        0.70
-  - model:           underwoods/medius-erebus-magnum-14b
-dtype:               bfloat16
-out_dtype:           bfloat16
----
-name:                lamarck-14b-converge-della                # This is the strongest control point to quickly
-merge_method:        della                                     # re-balance reasoning vs. prose
-base_model:          arcee-ai/Virtuoso-Small
-tokenizer_source:    arcee-ai/Virtuoso-Small
-parameters:
-  int8_mask:         false
-  normalize:         true
-  rescale:           false
-  density:           0.30
-  weight:            0.50
-  epsilon:           0.08
-  lambda:            1.00
-models:
-  - model:           sometimesanotion/lamarck-14b-reason-della
-    parameters:
-      density:       0.80
-      weight:        1.00
-  - model:           arcee-ai/Virtuoso-Small
-    parameters:
-      density:       0.40
-      weight:        0.50
-  - model:           sometimesanotion/lamarck-14b-prose-della
-    parameters:
-      density:       0.10
-      weight:        0.40
-dtype:               bfloat16
-out_dtype:           bfloat16
----
-name:                lamarck-14b-converge                     # Virtuoso has good capabilities all-around; it is 100% of the first 
-merge_method:        slerp                                    # two layers, and blends into the reasoning+prose convergance 
-base_model:          arcee-ai/Virtuoso-Small                  # for some interesting boosts
-tokenizer_source:    base
-parameters:
-  t:                 [ 0.00, 0.60, 0.80, 0.80, 0.80, 0.70, 0.40 ]
-slices:
-  - sources:
-    - layer_range:   [ 0, 2 ]
-      model:         arcee-ai/Virtuoso-Small
-    - layer_range:   [ 0, 2 ]
-      model:         merges/lamarck-14b-converge-della
-    t:               [ 0.00, 0.00 ]
-  - sources:
-    - layer_range:   [ 2, 8 ]
-      model:         arcee-ai/Virtuoso-Small
-    - layer_range:   [ 2, 8 ]
-      model:         merges/lamarck-14b-converge-della
-    t:               [ 0.00, 0.60 ]
-  - sources:
-    - layer_range:   [ 8, 16 ]
-      model:         arcee-ai/Virtuoso-Small
-    - layer_range:   [ 8, 16 ]
-      model:         merges/lamarck-14b-converge-della
-    t:               [ 0.60, 0.70 ]
-  - sources:
-    - layer_range:   [ 16, 24 ]
-      model:         arcee-ai/Virtuoso-Small
-    - layer_range:   [ 16, 24 ]
-      model:         merges/lamarck-14b-converge-della
-    t:               [ 0.70, 0.70 ]
-  - sources:
-    - layer_range:   [ 24, 32 ]
-      model:         arcee-ai/Virtuoso-Small
-    - layer_range:   [ 24, 32 ]
-      model:         merges/lamarck-14b-converge-della
-    t:               [ 0.70, 0.70 ]
-  - sources:
-    - layer_range:   [ 32, 40 ]
-      model:         arcee-ai/Virtuoso-Small
-    - layer_range:   [ 32, 40 ]
-      model:         merges/lamarck-14b-converge-della
-    t:               [ 0.70, 0.60 ]
-  - sources:
-    - layer_range:   [ 40, 48 ]
-      model:         arcee-ai/Virtuoso-Small
-    - layer_range:   [ 40, 48 ]
-      model:         merges/lamarck-14b-converge-della
-    t:               [ 0.60, 0.40 ]
-dtype:               bfloat16
-out_dtype:           bfloat16
----
-name:                lamarck-14b-finalize
-merge_method:        ties
-base_model:          Qwen/Qwen2.5-14B
-tokenizer_source:    Qwen/Qwen2.5-14B-Instruct
-parameters:
-  int8_mask:         false
-  normalize:         true
-  rescale:           false
-  density:           1.00
-  weight:            1.00
-models:
-  - model:           merges/lamarck-14b-converge
-dtype:               bfloat16
-out_dtype:           bfloat16
----
-
-```
 # [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
 Detailed results can be found [here](https://huggingface.co/datasets/open-llm-leaderboard/details_sometimesanotion__Lamarck-14B-v0.3)