Update README.md

README.md

@@ -1,3 +1,71 @@
 ---
 license: apache-2.0
+tags:
+- moe
+- merge
+- mergekit
+- lazymergekit
+- mlabonne/NeuralBeagle14-7B
+- mlabonne/NeuralDaredevil-7B
 ---
+
+---
+**This is a repository of GGUF Quants for DareBeagel-2x7B**
+---
+
+**Available Quants**
+
+* F16
+* Q8_0
+* Q6_K
+* Q5_0
+* Q5_K_M
+* Q5_K_S
+* Q4_0
+* Q4_K_M
+* Q4_K_S
+* Q3_K_M
+* Q3_K_S
+* Q2_K
+
+# Beyonder-2x7B-v2
+
+Beyonder-2x7B-v2 is a Mixure of Experts (MoE) made with the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
+* [mlabonne/NeuralBeagle14-7B](https://huggingface.co/mlabonne/NeuralBeagle14-7B)
+* [mlabonne/NeuralDaredevil-7B](https://huggingface.co/mlabonne/NeuralDaredevil-7B)
+
+## 🧩 Configuration
+
+```yaml
+base_model: mlabonne/NeuralBeagle14-7B
+gate_mode: random
+experts:
+  - source_model: mlabonne/NeuralBeagle14-7B
+    positive_prompts: [""]
+  - source_model: mlabonne/NeuralDaredevil-7B
+    positive_prompts: [""]
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers bitsandbytes accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "shadowml/Beyonder-2x7B-v2"
+
+tokenizer = AutoTokenizer.from_pretrained(model)
+pipeline = transformers.pipeline(
+    "text-generation",
+    model=model,
+    model_kwargs={"torch_dtype": torch.float16, "load_in_4bit": True},
+)
+
+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"])
+```