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README.md

@@ -1,3 +1,110 @@
-![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/X1tDlFYMMFPNI_YkDXYbE.png)
+---
+license: other
+tags:
+- merge
+- mergekit
+- lazymergekit
+base_model:
+- meta-llama/Meta-Llama-3-120B-Instruct
+- meta-llama/Meta-Llama-3-120B-Instruct
+- meta-llama/Meta-Llama-3-120B-Instruct
+- meta-llama/Meta-Llama-3-120B-Instruct
+- meta-llama/Meta-Llama-3-120B-Instruct
+- meta-llama/Meta-Llama-3-120B-Instruct
+- meta-llama/Meta-Llama-3-120B-Instruct
+- meta-llama/Meta-Llama-3-120B-Instruct
+- meta-llama/Meta-Llama-3-120B-Instruct
+- meta-llama/Meta-Llama-3-120B-Instruct
+- meta-llama/Meta-Llama-3-120B-Instruct
+- meta-llama/Meta-Llama-3-120B-Instruct
+- meta-llama/Meta-Llama-3-120B-Instruct
+---
 
-# Meta-Llama-3-220B-Instruct
+# Meta-Llama-3-220B-Instruct
+
+Meta-Llama-3-220B-Instruct is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
+* [meta-llama/Meta-Llama-3-120B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-120B-Instruct)
+* [meta-llama/Meta-Llama-3-120B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-120B-Instruct)
+* [meta-llama/Meta-Llama-3-120B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-120B-Instruct)
+* [meta-llama/Meta-Llama-3-120B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-120B-Instruct)
+* [meta-llama/Meta-Llama-3-120B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-120B-Instruct)
+* [meta-llama/Meta-Llama-3-120B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-120B-Instruct)
+* [meta-llama/Meta-Llama-3-120B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-120B-Instruct)
+* [meta-llama/Meta-Llama-3-120B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-120B-Instruct)
+* [meta-llama/Meta-Llama-3-120B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-120B-Instruct)
+* [meta-llama/Meta-Llama-3-120B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-120B-Instruct)
+* [meta-llama/Meta-Llama-3-120B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-120B-Instruct)
+* [meta-llama/Meta-Llama-3-120B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-120B-Instruct)
+* [meta-llama/Meta-Llama-3-120B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-120B-Instruct)
+
+## 🧩 Configuration
+
+```yaml
+slices:
+- sources:
+  - layer_range: [0, 20]
+    model: meta-llama/Meta-Llama-3-120B-Instruct
+- sources:
+  - layer_range: [10, 30]
+    model: meta-llama/Meta-Llama-3-120B-Instruct
+- sources:
+  - layer_range: [20, 40]
+    model: meta-llama/Meta-Llama-3-120B-Instruct
+- sources:
+  - layer_range: [30, 50]
+    model: meta-llama/Meta-Llama-3-120B-Instruct
+- sources:
+  - layer_range: [40, 60]
+    model: meta-llama/Meta-Llama-3-120B-Instruct
+- sources:
+  - layer_range: [50, 70]
+    model: meta-llama/Meta-Llama-3-120B-Instruct
+- sources:
+  - layer_range: [60, 80]
+    model: meta-llama/Meta-Llama-3-120B-Instruct
+- sources:
+  - layer_range: [70, 90]
+    model: meta-llama/Meta-Llama-3-120B-Instruct
+- sources:
+  - layer_range: [80, 100]
+    model: meta-llama/Meta-Llama-3-120B-Instruct
+- sources:
+  - layer_range: [90, 110]
+    model: meta-llama/Meta-Llama-3-120B-Instruct
+- sources:
+  - layer_range: [100, 120]
+    model: meta-llama/Meta-Llama-3-120B-Instruct
+- sources:
+  - layer_range: [110, 130]
+    model: meta-llama/Meta-Llama-3-120B-Instruct
+- sources:
+  - layer_range: [120, 140]
+    model: meta-llama/Meta-Llama-3-120B-Instruct
+merge_method: passthrough
+dtype: float16
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "mlabonne/Meta-Llama-3-220B-Instruct"
+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"])
+```