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README.md

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+---
+license: apache-2.0
+tags:
+- Safetensors
+- mistral
+- text-generation-inference
+- merge
+- mistral
+- 7b
+- mistralai/Mistral-7B-Instruct-v0.1
+- teknium/CollectiveCognition-v1-Mistral-7B
+- transformers
+- pytorch
+- mistral
+- text-generation
+- mistral-7b
+- instruct
+- finetune
+- gpt4
+- synthetic data
+- distillation
+- sharegpt
+- en
+- dataset:CollectiveCognition/chats-data-2023-09-27
+- base_model:mistralai/Mistral-7B-v0.1
+- license:apache-2.0
+- autotrain_compatible
+- endpoints_compatible
+- has_space
+- text-generation-inference
+- region:us
+---
+
+# CollectiveCognition-v1-Mistral-7B-Mistral-7B-Instruct-v0.1
+
+CollectiveCognition-v1-Mistral-7B-Mistral-7B-Instruct-v0.1 is a merge of the following models:
+* [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1)
+* [teknium/CollectiveCognition-v1-Mistral-7B](https://huggingface.co/teknium/CollectiveCognition-v1-Mistral-7B)
+
+## 🧩 Configuration
+
+```yaml
+slices:
+  - sources:
+      - model: mistralai/Mistral-7B-Instruct-v0.1
+        layer_range: [0, 32]
+      - model: teknium/CollectiveCognition-v1-Mistral-7B
+        layer_range: [0, 32]
+merge_method: slerp
+base_model: mistralai/Mistral-7B-Instruct-v0.1
+parameters:
+  t:
+    - filter: self_attn
+      value: [0, 0.5, 0.3, 0.7, 1]
+    - filter: mlp
+      value: [1, 0.5, 0.7, 0.3, 0]
+    - value: 0.5
+dtype: bfloat16
+```
+
+
+## 💻 Usage
+
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "MaziyarPanahi/CollectiveCognition-v1-Mistral-7B-Mistral-7B-Instruct-v0.1"
+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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+{
+  "_name_or_path": "mistralai/Mistral-7B-Instruct-v0.1",
+  "architectures": [
+    "MistralForCausalLM"
+  ],
+  "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": "mistral",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "rms_norm_eps": 1e-05,
+  "rope_theta": 10000.0,
+  "sliding_window": 4096,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.36.2",
+  "use_cache": true,
+  "vocab_size": 32000
+}

mergekit_config.yml

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+
+slices:
+  - sources:
+      - model: mistralai/Mistral-7B-Instruct-v0.1
+        layer_range: [0, 32]
+      - model: teknium/CollectiveCognition-v1-Mistral-7B
+        layer_range: [0, 32]
+merge_method: slerp
+base_model: mistralai/Mistral-7B-Instruct-v0.1
+parameters:
+  t:
+    - filter: self_attn
+      value: [0, 0.5, 0.3, 0.7, 1]
+    - filter: mlp
+      value: [1, 0.5, 0.7, 0.3, 0]
+    - value: 0.5
+dtype: bfloat16

model-00001-of-00002.safetensors

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+size 9942981696

model-00002-of-00002.safetensors

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model.safetensors.index.json

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