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README.md

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+---
+license: other
+tags:
+- merge
+- mergekit
+- lazymergekit
+base_model:
+- meta-llama/Meta-Llama-3-70B-Instruct
+- meta-llama/Meta-Llama-3-70B-Instruct
+- meta-llama/Meta-Llama-3-70B-Instruct
+- meta-llama/Meta-Llama-3-70B-Instruct
+- meta-llama/Meta-Llama-3-70B-Instruct
+- meta-llama/Meta-Llama-3-70B-Instruct
+- meta-llama/Meta-Llama-3-70B-Instruct
+---
+
+![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/C-Xw_m97bhXaTA1TEpHB7.jpeg)
+
+# Meta-Llama-3-120B-Instruct
+
+Meta-Llama-3-120B-Instruct is a [meta-llama/Meta-Llama-3-70B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-70B-Instruct) self-merge made with [MergeKit](https://github.com/arcee-ai/mergekit/tree/main).
+
+It was inspired by large merges like:
+
+- [alpindale/goliath-120b](https://huggingface.co/alpindale/goliath-120b)
+- [nsfwthrowitaway69/Venus-120b-v1.0](https://huggingface.co/nsfwthrowitaway69/Venus-120b-v1.0)
+- [cognitivecomputations/MegaDolphin-120b](https://huggingface.co/cognitivecomputations/MegaDolphin-120b)
+- [wolfram/miquliz-120b-v2.0](https://huggingface.co/wolfram/miquliz-120b-v2.0).
+
+Special thanks to [Eric Hartford](https://huggingface.co/ehartford) for both inspiring and evaluating this model and to [Charles Goddard](https://huggingface.co/chargoddard) for creating MergeKit.
+
+## 🔍 Applications
+
+I recommend using this model for creative writing. It uses the Llama 3 chat template with a default context window of 8K (can be extended with rope theta).
+
+Check the examples in the evaluation section to get an idea of its performance. The model is generally quite unhinged but has a good writing style. It sometimes outputs typos and is a big fan of uppercase.
+
+## ⚡ Quantized models
+
+Thanks to [Bartowski](https://huggingface.co/ehartford), [elinas](https://huggingface.co/elinas), the [mlx-community](https://huggingface.co/mlx-community) and others for providing these models.
+
+* **GGUF**: https://huggingface.co/lmstudio-community/Meta-Llama-3-120B-Instruct-GGUF
+* **EXL2**: https://huggingface.co/elinas/Meta-Llama-3-120B-Instruct-4.0bpw-exl2
+* **mlx**: https://huggingface.co/mlx-community/Meta-Llama-3-120B-Instruct-4bit
+
+## 🏆 Evaluation
+
+This model is great for creative writing but struggles in other tasks. I'd say use it with caution and don't expect it to outperform GPT-4 outside of some very specific use cases.
+
+* **X thread by Eric Hartford (creative writing)**: https://twitter.com/erhartford/status/1787050962114207886
+* **X thread by Daniel Kaiser (creative writing)**: https://twitter.com/spectate_or/status/1787257261309518101
+* **X thread by Simon (reasoning)**: https://twitter.com/NewDigitalEdu/status/1787403266894020893
+* **r/LocalLLaMa**: https://www.reddit.com/r/LocalLLaMA/comments/1cl525q/goliath_lovers_where_is_the_feedback_about/
+
+### Creative Writing
+
+Thanks to [Sam Paech](https://huggingface.co/sam-paech) for evaluating this model and sending me his outputs! 
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/61b8e2ba285851687028d395/-LJ7ivCRIPR1ur-LJHk3m.png)
+
+## 🧩 Configuration
+
+```yaml
+slices:
+- sources:
+  - layer_range: [0, 20]
+    model: meta-llama/Meta-Llama-3-70B-Instruct
+- sources:
+  - layer_range: [10, 30]
+    model: meta-llama/Meta-Llama-3-70B-Instruct
+- sources:
+  - layer_range: [20, 40]
+    model: meta-llama/Meta-Llama-3-70B-Instruct
+- sources:
+  - layer_range: [30, 50]
+    model: meta-llama/Meta-Llama-3-70B-Instruct
+- sources:
+  - layer_range: [40, 60]
+    model: meta-llama/Meta-Llama-3-70B-Instruct
+- sources:
+  - layer_range: [50, 70]
+    model: meta-llama/Meta-Llama-3-70B-Instruct
+- sources:
+  - layer_range: [60, 80]
+    model: meta-llama/Meta-Llama-3-70B-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-3-120B-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"])
+```

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