Quant for 3.5

README.md

@@ -1,57 +1,11 @@
 ---
 license: cc-by-nc-2.0
-quantized_by: bartowski
-pipeline_tag: text-generation
 ---
 
-## Exllama v2 Quantizations of laserxtral
+An experimentation regarding 'lasering' each expert to denoise and enhance model capabilities.
 
-Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.0.11">turboderp's ExLlamaV2 v0.0.11</a> for quantization.
+This follows the implementation of laserRMT @ https://github.com/cognitivecomputations/laserRMT
 
-# The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)
+Here, we are controlling layers checking which ones have lower signal to noise ratios (which are more subject to noise), to apply Laser interventions, still using Machenko Pastur to calculate this ratio.
 
-Each branch contains an individual bits per weight, with the main one containing only the meaurement.json for further conversions.
-
-Conversion was done using the default calibration dataset.
-
-Default arguments used except when the bits per weight is above 6.0, at that point the lm_head layer is quantized at 8 bits per weight instead of the default 6.
-
-Original model: https://huggingface.co/cognitivecomputations/laserxtral
-
-
-
-<a href="https://huggingface.co/bartowski/laserxtral-exl2/tree/6_5">6.5 bits per weight</a>
-
-<a href="https://huggingface.co/bartowski/laserxtral-exl2/tree/4_25">4.25 bits per weight</a>
-
-<a href="https://huggingface.co/bartowski/laserxtral-exl2/tree/3_5">3.5 bits per weight</a>
-
-<a href="https://huggingface.co/bartowski/laserxtral-exl2/tree/3_0">3.0 bits per weight</a>
-
-## Download instructions
-
-With git:
-
-```shell
-git clone --single-branch --branch 4_0 https://huggingface.co/bartowski/laserxtral-exl2
-```
-
-With huggingface hub (credit to TheBloke for instructions):
-
-```shell
-pip3 install huggingface-hub
-```
-
-To download the `main` (only useful if you only care about measurement.json) branch to a folder called `laserxtral-exl2`:
-
-```shell
-mkdir laserxtral-exl2
-huggingface-cli download bartowski/laserxtral-exl2 --local-dir laserxtral-exl2 --local-dir-use-symlinks False
-```
-
-To download from a different branch, add the `--revision` parameter:
-
-```shell
-mkdir laserxtral-exl2
-huggingface-cli download bartowski/laserxtral-exl2 --revision 4_0 --local-dir laserxtral-exl2 --local-dir-use-symlinks False
-```
+We are looking forward to measure its evaluation over the most important benchmarks.

config.json

@@ -0,0 +1,30 @@
+{
+  "_name_or_path": "mlabonne/Marcoro14-7B-slerp",
+  "architectures": [
+    "MixtralForCausalLM"
+  ],
+  "attention_dropout": 0.0,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 32768,
+  "model_type": "mixtral",
+  "num_attention_heads": 32,
+  "num_experts_per_tok": 2,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "num_local_experts": 4,
+  "output_router_logits": false,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 10000.0,
+  "router_aux_loss_coef": 0.001,
+  "sliding_window": null,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.36.2",
+  "use_cache": true,
+  "vocab_size": 32000
+}

mergekit_moe_config.yml

@@ -0,0 +1,35 @@
+base_model: mlabonne/Marcoro14-7B-slerp
+gate_mode: hidden # one of "hidden", "cheap_embed", or "random"
+dtype: bfloat16 # output dtype (float32, float16, or bfloat16)
+experts:
+  - source_model: ../laserRMT/laser_model_dolphindpo_new2
+    positive_prompts:
+    - "chat"
+    - "assistant"
+    - "tell me"
+    - "explain"
+  - source_model: ../laserRMT/laser_model_codeninja_new
+    positive_prompts:
+    - "code"
+    - "python"
+    - "javascript"
+    - "programming"
+    - "algorithm"
+  - source_model: ../laserRMT/laser_model_qbert_new
+    positive_prompts:
+    - "storywriting"
+    - "write"
+    - "scene"
+    - "story"
+    - "character"
+  - source_model: ../laserRMT/laser_model_wizardm
+    positive_prompts:
+    - "reason"
+    - "math"
+    - "mathematics"
+    - "solve"
+    - "count"
+
+# 
+# To run this
+# mergekit-moe --trust-remote-code --random-seed 0 ./moe_laser.yml ./moe_laser

model.safetensors.index.json

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