Add model files

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+tokenizer.json filter=lfs diff=lfs merge=lfs -text

README.md

@@ -1,3 +1,58 @@
----
-license: llama3.1
----
+---
+license: llama3.1
+base_model:
+- DreadPoor/LemonP-8B-Model_Stock
+- Youlln/1PARAMMYL-8B-ModelStock
+- jaspionjader/f-2-8b
+- Etherll/SuperHermes
+- meta-llama/Llama-3.1-8B-Instruct
+tags:
+- merge
+- mergekit
+---
+# Llama 3.1 Daredevilish Instruct
+
+- This model is an experimental Llama 3.1-based merge, inspired by the approach used in [mlabonne/Daredevil-8B](https://huggingface.co/mlabonne/Daredevil-8B).
+- It combines top-performing Llama 3.1 8B models on the MMLU-Pro benchmark from the [Open LLM Leaderboard](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard#/) as of January 21, 2025.
+- Its straightforward language makes it accessible and potentially valuable for everyday use.
+
+## Model Details
+
+- **Architecture:** Llama 3.1 (8.03B parameters)
+- **Training:** Merged from top MMLU-Pro models without additional finetuning
+- **Release Date:** January 21, 2025
+
+## Merge Configuration
+
+The model was created using [mergekit](https://github.com/arcee-ai/mergekit) with the following merge configuration:
+
+```yaml
+models:
+  - model: DreadPoor/LemonP-8B-Model_Stock
+    parameters:
+      density: 0.6
+      weight: 0.16
+  - model: Youlln/1PARAMMYL-8B-ModelStock
+    parameters:
+      density: 0.6
+      weight: 0.13
+  - model: jaspionjader/f-2-8b
+    parameters:
+      density: 0.6
+      weight: 0.10
+  - model: Etherll/SuperHermes
+    parameters:
+      density: 0.6
+      weight: 0.08
+merge_method: dare_ties
+base_model: meta-llama/Llama-3.1-8B-Instruct
+dtype: bfloat16
+```
+
+## Usage and Limitations
+
+This experimental model is designed for research and development purposes. Users should be aware of potential biases and limitations inherent in language models. Always validate outputs and use the model responsibly.
+
+## Future Work
+
+Further evaluation and fine-tuning may be necessary to optimize performance across various tasks. Researchers are encouraged to build upon this experimental merge to advance the capabilities of Llama-based models.

config.json

@@ -0,0 +1,40 @@
+{
+  "_name_or_path": "/drive2/Meta-Llama-3.1-8B-Instruct",
+  "architectures": [
+    "LlamaForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "bos_token_id": 128000,
+  "eos_token_id": [
+    128001,
+    128008,
+    128009
+  ],
+  "head_dim": 128,
+  "hidden_act": "silu",
+  "hidden_size": 4096,
+  "initializer_range": 0.02,
+  "intermediate_size": 14336,
+  "max_position_embeddings": 131072,
+  "mlp_bias": false,
+  "model_type": "llama",
+  "num_attention_heads": 32,
+  "num_hidden_layers": 32,
+  "num_key_value_heads": 8,
+  "pretraining_tp": 1,
+  "rms_norm_eps": 1e-05,
+  "rope_scaling": {
+    "factor": 8.0,
+    "high_freq_factor": 4.0,
+    "low_freq_factor": 1.0,
+    "original_max_position_embeddings": 8192,
+    "rope_type": "llama3"
+  },
+  "rope_theta": 500000.0,
+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.47.1",
+  "use_cache": true,
+  "vocab_size": 128256
+}

mergekit_config.yml

@@ -0,0 +1,22 @@
+models:
+#  - model: /drive2/Meta-Llama-3.1-8B
+    # No parameters necessary for base model
+  - model: /drive2/LemonP-8B-Model_Stock
+    parameters:
+      density: 0.6
+      weight: 0.16
+  - model: /drive2/1PARAMMYL-8B-ModelStock
+    parameters:
+      density: 0.6
+      weight: 0.13
+  - model: /drive2/f-2-8b
+    parameters:
+      density: 0.6
+      weight: 0.10
+  - model: /drive2/SuperHermes
+    parameters:
+      density: 0.6
+      weight: 0.08
+merge_method: dare_ties
+base_model: /drive2/Meta-Llama-3.1-8B-Instruct
+dtype: bfloat16

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