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README.md

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+---
+tags:
+- merge
+- mergekit
+- lazymergekit
+- microsoft/codebert-base
+- EleutherAI/gpt-neo-x-20b
+- openai/codex
+- bigscience/bloom
+- google/jurassic-1-jumbo
+- google/t5-v1_1-large
+- facebook/bart-large
+base_model:
+- microsoft/codebert-base
+- EleutherAI/gpt-neo-x-20b
+- openai/codex
+- bigscience/bloom
+- google/jurassic-1-jumbo
+- google/t5-v1_1-large
+- facebook/bart-large
+---
+
+# code-slerp
+
+code-slerp is a merge of the following models using [LazyMergekit](https://colab.research.google.com/drive/1obulZ1ROXHjYLn6PPZJwRR6GzgQogxxb?usp=sharing):
+* [microsoft/codebert-base](https://huggingface.co/microsoft/codebert-base)
+* [EleutherAI/gpt-neo-x-20b](https://huggingface.co/EleutherAI/gpt-neo-x-20b)
+* [openai/codex](https://huggingface.co/openai/codex)
+* [bigscience/bloom](https://huggingface.co/bigscience/bloom)
+* [google/jurassic-1-jumbo](https://huggingface.co/google/jurassic-1-jumbo)
+* [google/t5-v1_1-large](https://huggingface.co/google/t5-v1_1-large)
+* [facebook/bart-large](https://huggingface.co/facebook/bart-large)
+
+## 🧩 Configuration
+
+```yaml
+slices:
+  - sources:
+      - model: microsoft/codebert-base
+        layer_range: [0, 32]
+      - model: EleutherAI/gpt-neo-x-20b
+        layer_range: [0, 32]
+      - model: openai/codex
+        layer_range: [0, 32]
+      - model: bigscience/bloom
+        layer_range: [0, 32]
+      - model: google/jurassic-1-jumbo
+        layer_range: [0, 32]
+      - model: google/t5-v1_1-large
+        layer_range: [0, 32]
+      - model: facebook/bart-large
+        layer_range: [0, 32]
+merge_method: slerp
+base_model: microsoft/codebert-base
+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/code-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"])
+```