jcorenday
/

Daredevil-8B-4.0bpw-exl2

+---
+base_model:
+- nbeerbower/llama-3-stella-8B
+- Hastagaras/llama-3-8b-okay
+- nbeerbower/llama-3-gutenberg-8B
+- openchat/openchat-3.6-8b-20240522
+- Kukedlc/NeuralLLaMa-3-8b-DT-v0.1
+- cstr/llama3-8b-spaetzle-v20
+- mlabonne/ChimeraLlama-3-8B-v3
+- flammenai/Mahou-1.1-llama3-8B
+- KingNish/KingNish-Llama3-8b
+license: other
+tags:
+- merge
+- mergekit
+- lazymergekit
+- autoquant
+- exl2
+model-index:
+- name: Daredevil-8B
+  results:
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: AI2 Reasoning Challenge (25-Shot)
+      type: ai2_arc
+      config: ARC-Challenge
+      split: test
+      args:
+        num_few_shot: 25
+    metrics:
+    - type: acc_norm
+      value: 68.86
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Daredevil-8B
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: HellaSwag (10-Shot)
+      type: hellaswag
+      split: validation
+      args:
+        num_few_shot: 10
+    metrics:
+    - type: acc_norm
+      value: 84.5
+      name: normalized accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Daredevil-8B
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: MMLU (5-Shot)
+      type: cais/mmlu
+      config: all
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 69.24
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Daredevil-8B
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: TruthfulQA (0-shot)
+      type: truthful_qa
+      config: multiple_choice
+      split: validation
+      args:
+        num_few_shot: 0
+    metrics:
+    - type: mc2
+      value: 59.89
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Daredevil-8B
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: Winogrande (5-shot)
+      type: winogrande
+      config: winogrande_xl
+      split: validation
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 78.45
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Daredevil-8B
+      name: Open LLM Leaderboard
+  - task:
+      type: text-generation
+      name: Text Generation
+    dataset:
+      name: GSM8k (5-shot)
+      type: gsm8k
+      config: main
+      split: test
+      args:
+        num_few_shot: 5
+    metrics:
+    - type: acc
+      value: 73.54
+      name: accuracy
+    source:
+      url: https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard?query=mlabonne/Daredevil-8B
+      name: Open LLM Leaderboard
+---
+# Daredevil-8B
+![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/gFEhcIDSKa3AWpkNfH91q.jpeg)
+Daredevil-8B is a mega-merge designed to maximize MMLU. On 27 May 24, it is the Llama 3 8B model with the **highest MMLU score**.
+From my experience, a high MMLU score is all you need with Llama 3 models.
+It is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
+* [nbeerbower/llama-3-stella-8B](https://huggingface.co/nbeerbower/llama-3-stella-8B)
+* [Hastagaras/llama-3-8b-okay](https://huggingface.co/Hastagaras/llama-3-8b-okay)
+* [nbeerbower/llama-3-gutenberg-8B](https://huggingface.co/nbeerbower/llama-3-gutenberg-8B)
+* [openchat/openchat-3.6-8b-20240522](https://huggingface.co/openchat/openchat-3.6-8b-20240522)
+* [Kukedlc/NeuralLLaMa-3-8b-DT-v0.1](https://huggingface.co/Kukedlc/NeuralLLaMa-3-8b-DT-v0.1)
+* [cstr/llama3-8b-spaetzle-v20](https://huggingface.co/cstr/llama3-8b-spaetzle-v20)
+* [mlabonne/ChimeraLlama-3-8B-v3](https://huggingface.co/mlabonne/ChimeraLlama-3-8B-v3)
+* [flammenai/Mahou-1.1-llama3-8B](https://huggingface.co/flammenai/Mahou-1.1-llama3-8B)
+* [KingNish/KingNish-Llama3-8b](https://huggingface.co/KingNish/KingNish-Llama3-8b)
+Thanks to nbeerbower, Hastagaras, openchat, Kukedlc, cstr, flammenai, and KingNish for their merges. Special thanks to Charles Goddard and Arcee.ai for MergeKit.
+## 🔎 Applications
+You can use it as an improved version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct).
+This is a censored model. For an uncensored version, see [mlabonne/Daredevil-8B-abliterated](https://huggingface.co/mlabonne/Daredevil-8B-abliterated).
+Tested on LM Studio using the "Llama 3" preset.
+## ⚡ Quantization
+* **GGUF**: https://huggingface.co/mlabonne/Daredevil-8B-GGUF
+## 🏆 Evaluation
+### Open LLM Leaderboard
+Daredevil-8B is the best-performing 8B model on the Open LLM Leaderboard in terms of MMLU score (27 May 24).
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/xFKhGdSaIxL9_tcJPhM5w.png)
+### Nous
+Daredevil-8B is the best-performing 8B model on Nous' benchmark suite (evaluation performed using [LLM AutoEval](https://github.com/mlabonne/llm-autoeval), 27 May 24). See the entire leaderboard [here](https://huggingface.co/spaces/mlabonne/Yet_Another_LLM_Leaderboard).
+| Model | Average | AGIEval | GPT4All | TruthfulQA | Bigbench |
+|---|---:|---:|---:|---:|---:|
+| [**mlabonne/Daredevil-8B**](https://huggingface.co/mlabonne/Daredevil-8B) [📄](https://gist.github.com/mlabonne/080f9c5f153ea57a7ab7d932cf896f21) | **55.87** | **44.13** | **73.52** | **59.05** | **46.77** |
+| [mlabonne/Daredevil-8B-abliterated](https://huggingface.co/mlabonne/Daredevil-8B-abliterated) [📄](https://gist.github.com/mlabonne/32cdd8460804662c856bcb2a20acd49e) | 55.06 | 43.29 | 73.33 | 57.47 | 46.17 |
+| [mlabonne/Llama-3-8B-Instruct-abliterated-dpomix](https://huggingface.co/mlabonne/Llama-3-8B-Instruct-abliterated-dpomix) [📄](https://gist.github.com/mlabonne/d711548df70e2c04771cc68ab33fe2b9) | 52.26 | 41.6 | 69.95 | 54.22 | 43.26 |
+| [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) [📄](https://gist.github.com/mlabonne/8329284d86035e6019edb11eb0933628) | 51.34 | 41.22 | 69.86 | 51.65 | 42.64 |
+| [failspy/Meta-Llama-3-8B-Instruct-abliterated-v3](https://huggingface.co/failspy/Meta-Llama-3-8B-Instruct-abliterated-v3) [📄](https://gist.github.com/mlabonne/f46cce0262443365e4cce2b6fa7507fc) | 51.21 | 40.23 | 69.5 | 52.44 | 42.69 |
+| [mlabonne/OrpoLlama-3-8B](https://huggingface.co/mlabonne/OrpoLlama-3-8B) [📄](https://gist.github.com/mlabonne/22896a1ae164859931cc8f4858c97f6f) | 48.63 | 34.17 | 70.59 | 52.39 | 37.36 |
+| [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) [📄](https://gist.github.com/mlabonne/616b6245137a9cfc4ea80e4c6e55d847) | 45.42 | 31.1 | 69.95 | 43.91 | 36.7 |
+## 🌳 Model family tree
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/ekwRGgnjzEOyprT8sEBFt.png)
+## 🧩 Configuration
+```yaml
+models:
+  - model: NousResearch/Meta-Llama-3-8B
+    # No parameters necessary for base model
+  - model: nbeerbower/llama-3-stella-8B
+    parameters:
+      density: 0.6
+      weight: 0.16
+  - model: Hastagaras/llama-3-8b-okay
+    parameters:
+      density: 0.56
+      weight: 0.1
+  - model: nbeerbower/llama-3-gutenberg-8B
+    parameters:
+      density: 0.6
+      weight: 0.18
+  - model: openchat/openchat-3.6-8b-20240522
+    parameters:
+      density: 0.56
+      weight: 0.12
+  - model: Kukedlc/NeuralLLaMa-3-8b-DT-v0.1
+    parameters:
+      density: 0.58
+      weight: 0.18
+  - model: cstr/llama3-8b-spaetzle-v20
+    parameters:
+      density: 0.56
+      weight: 0.08
+  - model: mlabonne/ChimeraLlama-3-8B-v3
+    parameters:
+      density: 0.56
+      weight: 0.08
+  - model: flammenai/Mahou-1.1-llama3-8B
+    parameters:
+      density: 0.55
+      weight: 0.05
+  - model: KingNish/KingNish-Llama3-8b
+    parameters:
+      density: 0.55
+      weight: 0.05
+merge_method: dare_ties
+base_model: NousResearch/Meta-Llama-3-8B
+dtype: bfloat16
+```
+## 💻 Usage
+```python
+!pip install -qU transformers accelerate
+from transformers import AutoTokenizer
+import transformers
+import torch
+model = "mlabonne/Daredevil-8B"
+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.bfloat16,
+    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"])
+```