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README.md

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+---
+base_model:
+- ibm-granite/granite-3.3-2b-instruct
+- powermove72/granite-3.3-2b-Hermes3dataset
+tags:
+- merge
+- mergekit
+- lazymergekit
+- ibm-granite/granite-3.3-2b-instruct
+- powermove72/granite-3.3-2b-Hermes3dataset
+---
+
+# Granite-3.3-2B-Avg-SliceWeighted
+
+Granite-3.3-2B-Avg-SliceWeighted is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
+* [ibm-granite/granite-3.3-2b-instruct](https://huggingface.co/ibm-granite/granite-3.3-2b-instruct)
+* [powermove72/granite-3.3-2b-Hermes3dataset](https://huggingface.co/powermove72/granite-3.3-2b-Hermes3dataset)
+
+## 🧩 Configuration
+
+```yaml
+# ----------------------------------------------------------------------
+# merge_weighted_average_40layers.yaml
+#   Slice‑wise weighted‑average merge for a 40‑layer LLM.
+#   – Different contribution per layer range.
+# ----------------------------------------------------------------------
+merge_method: linear               # merge type
+
+# ----------------------------------------------------------------------
+# Global merge options
+# ----------------------------------------------------------------------
+dtype: bfloat16                               # preferred dtype on modern GPUs
+parameters:
+  normalize: true                           # make each slice’s weights sum to 1.0
+  low_cpu_mem_usage: true                    # stream weights, don’t load everything into RAM
+
+seed: 2025                                    # reproducibility
+deterministic: true                           # torch‑cudnn deterministic mode
+
+# ----------------------------------------------------------------------
+# Metadata (helps with provenance & experiment tracking)
+# ----------------------------------------------------------------------
+metadata:
+  model_name: Granite-3.3-2B-Avg-SliceWeighted
+  version: v1.0
+  date: 2025-08-15
+  notes: |
+    - 40‑layer model (indices 0‑39).
+    - Three slices:
+        * Layers 0‑13   → 80 % Llama‑2, 20 % Mistral
+        * Layers 14‑26  → 50 % each (mid‑point)
+        * Layers 27‑39  → 20 % Llama‑2, 80 % Mistral
+    - Normalised weights are enforced by `parameters.normalize`.
+    - Uses granite-3.3-2b-Hermes3dataset tokenizer for token‑id alignment.
+
+# ----------------------------------------------------------------------
+# Tokenizer – both source models share the same one, so we can safely force it.
+# ----------------------------------------------------------------------
+tokenizer_source: powermove72/granite-3.3-2b-Hermes3dataset
+
+# ----------------------------------------------------------------------
+# Slice definitions (non‑overlapping, each covers a contiguous block of layers)
+# ----------------------------------------------------------------------
+slices:
+  # --------------------------------------------------------------
+  # Slice 1: Layers 0‑13 (the first 14 transformer blocks)
+  # --------------------------------------------------------------
+  - sources:
+      - model: ibm-granite/granite-3.3-2b-instruct
+        layer_range: [0, 13]               
+        parameters:
+          weight: 0.8                       
+      - model: powermove72/granite-3.3-2b-Hermes3dataset
+        layer_range: [0, 13]
+        parameters:
+          weight: 0.2                       
+
+  # --------------------------------------------------------------
+  # Slice 2: Layers 14‑26 (the middle 13 transformer blocks)
+  # --------------------------------------------------------------
+  - sources:
+      - model: ibm-granite/granite-3.3-2b-instruct
+        layer_range: [13, 26]
+        parameters:
+          weight: 0.5                       # balanced
+      - model: powermove72/granite-3.3-2b-Hermes3dataset
+        layer_range: [13, 26]
+        parameters:
+          weight: 0.5
+
+  # --------------------------------------------------------------
+  # Slice 3: Layers 27‑39 (the last 14 transformer blocks)
+  # --------------------------------------------------------------
+  - sources:
+      - model: ibm-granite/granite-3.3-2b-instruct
+        layer_range: [26, 40]
+        parameters:
+          weight: 0.2                       
+      - model: powermove72/granite-3.3-2b-Hermes3dataset
+        layer_range: [26, 40]
+        parameters:
+          weight: 0.8                       
+
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "powermove72/Granite-3.3-2B-Avg-SliceWeighted"
+messages = [{"role": "user", "content": "What is a large language model?"}]
+
+tokenizer = AutoTokenizer.from_pretrained(model)
+prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+pipeline = transformers.pipeline(
+    "text-generation",
+    model=model,
+    torch_dtype=torch.float16,
+    device_map="auto",
+)
+
+outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
+print(outputs[0]["generated_text"])
+```

config.json

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+{
+  "architectures": [
+    "GraniteForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "attention_multiplier": 0.015625,
+  "bos_token_id": 0,
+  "embedding_multiplier": 12.0,
+  "eos_token_id": 0,
+  "hidden_act": "silu",
+  "hidden_size": 2048,
+  "initializer_range": 0.02,
+  "intermediate_size": 8192,
+  "logits_scaling": 8.0,
+  "max_position_embeddings": 131072,
+  "mlp_bias": false,
+  "model_type": "granite",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 40,
+  "num_key_value_heads": 8,
+  "pad_token_id": 0,
+  "residual_multiplier": 0.22,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": null,
+  "rope_theta": 10000000.0,
+  "tie_word_embeddings": true,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.55.1",
+  "use_cache": true,
+  "vocab_size": 49152
+}

mergekit_config.yml

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+
+# ----------------------------------------------------------------------
+# merge_weighted_average_40layers.yaml
+#   Slice‑wise weighted‑average merge for a 40‑layer LLM.
+#   – Different contribution per layer range.
+# ----------------------------------------------------------------------
+merge_method: linear               # merge type
+
+# ----------------------------------------------------------------------
+# Global merge options
+# ----------------------------------------------------------------------
+dtype: bfloat16                               # preferred dtype on modern GPUs
+parameters:
+  normalize: true                           # make each slice’s weights sum to 1.0
+  low_cpu_mem_usage: true                    # stream weights, don’t load everything into RAM
+
+seed: 2025                                    # reproducibility
+deterministic: true                           # torch‑cudnn deterministic mode
+
+# ----------------------------------------------------------------------
+# Metadata (helps with provenance & experiment tracking)
+# ----------------------------------------------------------------------
+metadata:
+  model_name: Granite-3.3-2B-Avg-SliceWeighted
+  version: v1.0
+  date: 2025-08-15
+  notes: |
+    - 40‑layer model (indices 0‑39).
+    - Three slices:
+        * Layers 0‑13   → 80 % Llama‑2, 20 % Mistral
+        * Layers 14‑26  → 50 % each (mid‑point)
+        * Layers 27‑39  → 20 % Llama‑2, 80 % Mistral
+    - Normalised weights are enforced by `parameters.normalize`.
+    - Uses granite-3.3-2b-Hermes3dataset tokenizer for token‑id alignment.
+
+# ----------------------------------------------------------------------
+# Tokenizer – both source models share the same one, so we can safely force it.
+# ----------------------------------------------------------------------
+tokenizer_source: powermove72/granite-3.3-2b-Hermes3dataset
+
+# ----------------------------------------------------------------------
+# Slice definitions (non‑overlapping, each covers a contiguous block of layers)
+# ----------------------------------------------------------------------
+slices:
+  # --------------------------------------------------------------
+  # Slice 1: Layers 0‑13 (the first 14 transformer blocks)
+  # --------------------------------------------------------------
+  - sources:
+      - model: ibm-granite/granite-3.3-2b-instruct
+        layer_range: [0, 13]               
+        parameters:
+          weight: 0.8                       
+      - model: powermove72/granite-3.3-2b-Hermes3dataset
+        layer_range: [0, 13]
+        parameters:
+          weight: 0.2                       
+
+  # --------------------------------------------------------------
+  # Slice 2: Layers 14‑26 (the middle 13 transformer blocks)
+  # --------------------------------------------------------------
+  - sources:
+      - model: ibm-granite/granite-3.3-2b-instruct
+        layer_range: [13, 26]
+        parameters:
+          weight: 0.5                       # balanced
+      - model: powermove72/granite-3.3-2b-Hermes3dataset
+        layer_range: [13, 26]
+        parameters:
+          weight: 0.5
+
+  # --------------------------------------------------------------
+  # Slice 3: Layers 27‑39 (the last 14 transformer blocks)
+  # --------------------------------------------------------------
+  - sources:
+      - model: ibm-granite/granite-3.3-2b-instruct
+        layer_range: [26, 40]
+        parameters:
+          weight: 0.2                       
+      - model: powermove72/granite-3.3-2b-Hermes3dataset
+        layer_range: [26, 40]
+        parameters:
+          weight: 0.8                       
+

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special_tokens_map.json

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+}

tokenizer_config.json

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