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README.md

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+---
+tags:
+- merge
+- mergekit
+- lazymergekit
+- SuperAGI/SAM
+- GoogleAI/Gemini
+- bigscience/bloom
+- openai/opt-175b
+- deepmind/gopher
+- microsoft/megatron-turing-nlg
+base_model:
+- SuperAGI/SAM
+- GoogleAI/Gemini
+- bigscience/bloom
+- openai/opt-175b
+- deepmind/gopher
+- microsoft/megatron-turing-nlg
+---
+
+# SAM-Gemini-BLOOM-OPT-Gopher-Megatron-slerp
+
+SAM-Gemini-BLOOM-OPT-Gopher-Megatron-slerp is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
+* [SuperAGI/SAM](https://huggingface.co/SuperAGI/SAM)
+* [GoogleAI/Gemini](https://huggingface.co/GoogleAI/Gemini)
+* [bigscience/bloom](https://huggingface.co/bigscience/bloom)
+* [openai/opt-175b](https://huggingface.co/openai/opt-175b)
+* [deepmind/gopher](https://huggingface.co/deepmind/gopher)
+* [microsoft/megatron-turing-nlg](https://huggingface.co/microsoft/megatron-turing-nlg)
+
+## 🧩 Configuration
+
+```yaml
+slices:
+ - sources:
+ - model: SuperAGI/SAM
+ layer_range: [0, 32]
+ - model: GoogleAI/Gemini
+ layer_range: [0, 32]
+ - model: bigscience/bloom
+ layer_range: [0, 32]
+ - model: openai/opt-175b
+ layer_range: [0, 32]
+ - model: deepmind/gopher
+ layer_range: [0, 32]
+ - model: microsoft/megatron-turing-nlg
+ layer_range: [0, 32]
+merge_method: slerp
+base_model: SuperAGI/SAM
+parameters:
+ t:
+ - filter: self_attn
+ value: [0, 0.5, 0.3, 0.7, 1]
+ - filter: mlp
+ value: [1, 0.5, 0.7, 0.3, 0]
+ - value: 0.5
+dtype: bfloat1
+```
+
+## 💻 Usage
+
+```python
+!pip install -qU transformers accelerate
+
+from transformers import AutoTokenizer
+import transformers
+import torch
+
+model = "Or4cl3-1/SAM-Gemini-BLOOM-OPT-Gopher-Megatron-slerp"
+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"])
+```