Quant for 4.25

README.md

@@ -11,69 +11,109 @@ base_model:
 - beowolx/CodeNinja-1.0-OpenChat-7B
 - SanjiWatsuki/Kunoichi-DPO-v2-7B
 - mlabonne/NeuralDaredevil-7B
-quantized_by: bartowski
-pipeline_tag: text-generation
 ---
 
-## Exllama v2 Quantizations of Beyonder-4x7B-v3
-
-Using <a href="https://github.com/turboderp/exllamav2/releases/tag/v0.0.16">turboderp's ExLlamaV2 v0.0.16</a> for quantization.
-
-## The "main" branch only contains the measurement.json, download one of the other branches for the model (see below)
-
-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/mlabonne/Beyonder-4x7B-v3
-
-
-<a href="https://huggingface.co/bartowski/Beyonder-4x7B-v3-exl2/tree/8_0">8.0 bits per weight</a>
-
-<a href="https://huggingface.co/bartowski/Beyonder-4x7B-v3-exl2/tree/6_5">6.5 bits per weight</a>
-
-<a href="https://huggingface.co/bartowski/Beyonder-4x7B-v3-exl2/tree/5_0">5.0 bits per weight</a>
-
-<a href="https://huggingface.co/bartowski/Beyonder-4x7B-v3-exl2/tree/4_25">4.25 bits per weight</a>
-
-<a href="https://huggingface.co/bartowski/Beyonder-4x7B-v3-exl2/tree/3_5">3.5 bits per weight</a>
-
-
-## Download instructions
-
-With git:
-
-```shell
-git clone --single-branch --branch 6_5 https://huggingface.co/bartowski/Beyonder-4x7B-v3-exl2
+![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/9XVgxKyuXTQVO5mO-EOd4.jpeg)
+
+# 🔮 Beyonder-4x7B-v3
+
+Beyonder-4x7B-v3 is an improvement over the popular [Beyonder-4x7B-v2](https://huggingface.co/mlabonne/Beyonder-4x7B-v2). It's a Mixture of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
+* [mlabonne/AlphaMonarch-7B](https://huggingface.co/mlabonne/AlphaMonarch-7B)
+* [beowolx/CodeNinja-1.0-OpenChat-7B](https://huggingface.co/beowolx/CodeNinja-1.0-OpenChat-7B)
+* [SanjiWatsuki/Kunoichi-DPO-v2-7B](https://huggingface.co/SanjiWatsuki/Kunoichi-DPO-v2-7B)
+* [mlabonne/NeuralDaredevil-7B](https://huggingface.co/mlabonne/NeuralDaredevil-7B)
+
+Special thanks to [beowolx](https://huggingface.co/beowolx) for making the best Mistral-based code model and to [SanjiWatsuki](https://huggingface.co/SanjiWatsuki) for creating one of the very best RP models.
+
+## 🔍 Applications
+
+This model uses a context window of 8k. I recommend using it with the Mistral Instruct chat template (works perfectly with LM Studio).
+
+If you use SillyTavern, you might want to tweak the inference parameters. Here's what LM Studio uses as a reference: `temp` 0.8, `top_k` 40, `top_p` 0.95, `min_p` 0.05, `repeat_penalty` 1.1.
+
+Thanks to its four experts, it's a well-rounded model, capable of achieving most tasks. As two experts are always used to generate an answer, every task benefits from other capabilities, like chat with RP, or math with code.
+
+## ⚡ Quantized models
+
+* **GGUF**: https://huggingface.co/mlabonne/Beyonder-4x7B-v3-GGUF
+
+## 🏆 Evaluation
+
+### Nous
+
+Beyonder-4x7B-v3 is one of the best models on Nous' benchmark suite (evaluation performed using [LLM AutoEval](https://github.com/mlabonne/llm-autoeval)) and significantly outperforms the v2. See the entire leaderboard [here](https://huggingface.co/spaces/mlabonne/Yet_Another_LLM_Leaderboard).
+
+| Model | Average | AGIEval | GPT4All | TruthfulQA | Bigbench |
+|---|---:|---:|---:|---:|---:|
+| [mlabonne/AlphaMonarch-7B](https://huggingface.co/mlabonne/AlphaMonarch-7B) [📄](https://gist.github.com/mlabonne/1d33c86824b3a11d2308e36db1ba41c1) | 62.74 | 45.37 | 77.01 | 78.39 | 50.2 |
+| [**mlabonne/Beyonder-4x7B-v3**](https://huggingface.co/mlabonne/Beyonder-4x7B-v3) [📄](https://gist.github.com/mlabonne/3740020807e559f7057c32e85ce42d92) | **61.91** | **45.85** | **76.67** | **74.98** | **50.12** |
+| [mlabonne/NeuralDaredevil-7B](https://huggingface.co/mlabonne/NeuralDaredevil-7B) [📄](https://gist.github.com/mlabonne/cbeb077d1df71cb81c78f742f19f4155) | 59.39 | 45.23 | 76.2 | 67.61 | 48.52 |
+| [SanjiWatsuki/Kunoichi-DPO-v2-7B](https://huggingface.co/SanjiWatsuki/Kunoichi-DPO-v2-7B) [📄](https://gist.github.com/mlabonne/895ff5171e998abfdf2a41a4f9c84450) | 58.29 | 44.79 | 75.05 | 65.68 | 47.65 |
+| [mlabonne/Beyonder-4x7B-v2](https://huggingface.co/mlabonne/Beyonder-4x7B-v2) [📄](https://gist.github.com/mlabonne/f73baa140a510a676242f8a4496d05ca) | 57.13 | 45.29 | 75.95 | 60.86 | 46.4 |
+| [beowolx/CodeNinja-1.0-OpenChat-7B](https://huggingface.co/beowolx/CodeNinja-1.0-OpenChat-7B) [📄](https://gist.github.com/mlabonne/08b5280c221fbd7f98eb27561ae902a3) | 50.35 | 39.98 | 71.77 | 48.73 | 40.92 |
+
+### Open LLM Leaderboard
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/NFRYqzwuy9TB-s-Hy3gRy.png)
+
+## 🧩 Configuration
+
+```yaml
+base_model: mlabonne/AlphaMonarch-7B
+experts:
+  - source_model: mlabonne/AlphaMonarch-7B
+    positive_prompts:
+    - "chat"
+    - "assistant"
+    - "tell me"
+    - "explain"
+    - "I want"
+  - source_model: beowolx/CodeNinja-1.0-OpenChat-7B
+    positive_prompts:
+    - "code"
+    - "python"
+    - "javascript"
+    - "programming"
+    - "algorithm"
+  - source_model: SanjiWatsuki/Kunoichi-DPO-v2-7B
+    positive_prompts:
+    - "storywriting"
+    - "write"
+    - "scene"
+    - "story"
+    - "character"
+  - source_model: mlabonne/NeuralDaredevil-7B
+    positive_prompts:
+    - "reason"
+    - "math"
+    - "mathematics"
+    - "solve"
+    - "count"
 ```
 
-With huggingface hub (credit to TheBloke for instructions):
+## 💻 Usage
 
-```shell
-pip3 install huggingface-hub
-```
+```python
+!pip install -qU transformers bitsandbytes accelerate
 
-To download the `main` (only useful if you only care about measurement.json) branch to a folder called `Beyonder-4x7B-v3-exl2`:
+from transformers import AutoTokenizer
+import transformers
+import torch
 
-```shell
-mkdir Beyonder-4x7B-v3-exl2
-huggingface-cli download bartowski/Beyonder-4x7B-v3-exl2 --local-dir Beyonder-4x7B-v3-exl2 --local-dir-use-symlinks False
-```
+model = "mlabonne/Beyonder-4x7B-v3"
 
-To download from a different branch, add the `--revision` parameter:
+tokenizer = AutoTokenizer.from_pretrained(model)
+pipeline = transformers.pipeline(
+    "text-generation",
+    model=model,
+    model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
+)
 
-Linux:
-
-```shell
-mkdir Beyonder-4x7B-v3-exl2-6_5
-huggingface-cli download bartowski/Beyonder-4x7B-v3-exl2 --revision 6_5 --local-dir Beyonder-4x7B-v3-exl2-6_5 --local-dir-use-symlinks False
+messages = [{"role": "user", "content": "Explain what a Mixture of Experts is in less than 100 words."}]
+prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+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"])
 ```
+Output:
 
-Windows (which apparently doesn't like _ in folders sometimes?):
-
-```shell
-mkdir Beyonder-4x7B-v3-exl2-6.5
-huggingface-cli download bartowski/Beyonder-4x7B-v3-exl2 --revision 6_5 --local-dir Beyonder-4x7B-v3-exl2-6.5 --local-dir-use-symlinks False
-```
+> A Mixture of Experts (MoE) is a neural network architecture that tackles complex tasks by dividing them into simpler subtasks, delegating each to specialized expert modules. These experts learn to independently handle specific problem aspects. The MoE structure combines their outputs, leveraging their expertise for improved overall performance. This approach promotes modularity, adaptability, and scalability, allowing for better generalization in various applications.

config.json

@@ -0,0 +1,41 @@
+{
+    "_name_or_path": "mlabonne/AlphaMonarch-7B",
+    "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": "float16",
+    "transformers_version": "4.39.0",
+    "use_cache": true,
+    "vocab_size": 32000,
+    "quantization_config": {
+        "quant_method": "exl2",
+        "version": "0.0.16",
+        "bits": 4.25,
+        "head_bits": 6,
+        "calibration": {
+            "rows": 100,
+            "length": 2048,
+            "dataset": "(default)"
+        }
+    }
+}

mergekit_moe_config.yml

@@ -0,0 +1,31 @@
+
+base_model: mlabonne/AlphaMonarch-7B
+experts:
+  - source_model: mlabonne/AlphaMonarch-7B
+    positive_prompts:
+    - "chat"
+    - "assistant"
+    - "tell me"
+    - "explain"
+    - "I want"
+  - source_model: beowolx/CodeNinja-1.0-OpenChat-7B
+    positive_prompts:
+    - "code"
+    - "python"
+    - "javascript"
+    - "programming"
+    - "algorithm"
+  - source_model: SanjiWatsuki/Kunoichi-DPO-v2-7B
+    positive_prompts:
+    - "storywriting"
+    - "write"
+    - "scene"
+    - "story"
+    - "character"
+  - source_model: mlabonne/NeuralDaredevil-7B
+    positive_prompts:
+    - "reason"
+    - "math"
+    - "mathematics"
+    - "solve"
+    - "count"

model.safetensors.index.json

@@ -0,0 +1 @@
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