Model Upload

README.md

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+---
+license: cc-by-nc-4.0
+tags:
+- not-for-all-audiences
+- nsfw
+---
+
+First :
+```shell
+layer_slices:
+  - model: Undi95/MLewd-L2-Chat-13B
+    start: 0
+    end: 16
+  - model: Undi95/MLewd-ReMM-L2-Chat-20B-Part1
+    start: 8
+    end: 20
+  - model: Undi95/MLewd-L2-Chat-13B
+    start: 17
+    end: 32
+  - model: Undi95/MLewd-ReMM-L2-Chat-20B-Part1
+    start: 21
+    end: 40
+```
+
+Inverted:
+```shell
+layer_slices:
+  - model: Undi95/MLewd-ReMM-L2-Chat-20B-Part1
+    start: 0
+    end: 16
+  - model: Undi95/MLewd-L2-Chat-13B
+    start: 8
+    end: 20
+  - model: Undi95/MLewd-ReMM-L2-Chat-20B-Part1
+    start: 17
+    end: 32
+  - model: Undi95/MLewd-L2-Chat-13B
+    start: 21
+    end: 40
+```
+
+Precise:
+```shell
+layer_slices:
+  - model: Undi95/MLewd-L2-Chat-13B
+    start: 0
+    end: 8
+  - model: Undi95/MLewd-ReMM-L2-Chat-20B-Part1
+    start: 4
+    end: 12
+  - model: Undi95/MLewd-L2-Chat-13B
+    start: 9
+    end: 16
+  - model: Undi95/MLewd-ReMM-L2-Chat-20B-Part1
+    start: 13
+    end: 22
+  - model: Undi95/MLewd-L2-Chat-13B
+    start: 17
+    end: 24
+  - model: Undi95/MLewd-ReMM-L2-Chat-20B-Part1
+    start: 23
+    end: 32
+  - model: Undi95/MLewd-L2-Chat-13B
+    start: 25
+    end: 32
+  - model: Undi95/MLewd-ReMM-L2-Chat-20B-Part1
+    start: 33
+    end: 40
+```
+
+PreciseInverted:
+```shell
+layer_slices:
+  - model: Undi95/MLewd-ReMM-L2-Chat-20B-Part1
+    start: 0
+    end: 8
+  - model: Undi95/MLewd-L2-Chat-13B
+    start: 4
+    end: 12
+  - model: Undi95/MLewd-ReMM-L2-Chat-20B-Part1
+    start: 9
+    end: 16
+  - model: Undi95/MLewd-L2-Chat-13B
+    start: 13
+    end: 22
+  - model: Undi95/MLewd-ReMM-L2-Chat-20B-Part1
+    start: 17
+    end: 24
+  - model: Undi95/MLewd-L2-Chat-13B
+    start: 23
+    end: 32
+  - model: Undi95/MLewd-ReMM-L2-Chat-20B-Part1
+    start: 25
+    end: 32
+  - model: Undi95/MLewd-L2-Chat-13B
+    start: 33
+    end: 40
+```
+
+Part1 = ReMM v2.1 merged /w MLewd low weight to keep consistency. I call this "dilution" and result show consistency and coherency without repeat/loop beside the small amount of duplicated datas.
+
+The goal is to find the best way to interlace layers the best way possible to have a sweetspot between 13B and +30B.
+
+Normal/Inverted is by chunk of 16 layers and Precise/PreciseInverted is by chunk of 8 layers.
+
+All the models are made of 64(+1) layers. Need testing.
+
+## Prompt template: Alpaca
+
+```
+Below is an instruction that describes a task. Write a response that completes the request.
+
+### Instruction:
+{prompt}
+
+### Response:
+```

config.json

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+{
+  "_name_or_path": "Undi95/MLewd-L2-Chat-13B",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 5120,
+  "initializer_range": 0.02,
+  "intermediate_size": 13824,
+  "max_position_embeddings": 4096,
+  "model_type": "llama",
+  "num_attention_heads": 40,
+  "num_hidden_layers": 62,
+  "num_key_value_heads": 40,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 10000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "float16",
+  "transformers_version": "4.33.2",
+  "use_cache": true,
+  "vocab_size": 32000
+}

output.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:2d1fe765b914c13eea8392433d5ae9dcfbc8dcc90483842d3067d42818dc040a
+size 7846525560

pytorch_model.bin.index.json

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