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  ---
 
 
 
 
 
 
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  base_model:
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  - nlpguy/AlloyIngotNeoY
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  - yam-peleg/Experiment24-7B
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- library_name: transformers
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- tags:
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- - mergekit
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- - merge
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-
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  ---
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- # merge
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-
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- This is a merge of pre-trained language models created using [mergekit](https://github.com/cg123/mergekit).
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-
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- ## Merge Details
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- ### Merge Method
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- This model was merged using the SLERP merge method.
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- ### Models Merged
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-
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- The following models were included in the merge:
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  * [nlpguy/AlloyIngotNeoY](https://huggingface.co/nlpguy/AlloyIngotNeoY)
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  * [yam-peleg/Experiment24-7B](https://huggingface.co/yam-peleg/Experiment24-7B)
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- ### Configuration
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-
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- The following YAML configuration was used to produce this model:
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  ```yaml
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-
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  slices:
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  - sources:
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  - model: nlpguy/AlloyIngotNeoY
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  - value: 0.5
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  dtype: bfloat16
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  random_seed: 0
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-
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- ```
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+ license: apache-2.0
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+ tags:
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+ - merge
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+ - mergekit
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+ - lazymergekit
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+ - automerger
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  base_model:
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  - nlpguy/AlloyIngotNeoY
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  - yam-peleg/Experiment24-7B
 
 
 
 
 
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  ---
 
 
 
 
 
 
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+ # AlloyingotneoyExperiment24-7B
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+ AlloyingotneoyExperiment24-7B is an automated merge created by [Maxime Labonne](https://huggingface.co/mlabonne) using the following configuration.
 
 
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  * [nlpguy/AlloyIngotNeoY](https://huggingface.co/nlpguy/AlloyIngotNeoY)
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  * [yam-peleg/Experiment24-7B](https://huggingface.co/yam-peleg/Experiment24-7B)
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+ ## 🧩 Configuration
 
 
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  ```yaml
 
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  slices:
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  - sources:
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  - model: nlpguy/AlloyIngotNeoY
 
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  - value: 0.5
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  dtype: bfloat16
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  random_seed: 0
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+ ```
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+
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+ ## 💻 Usage
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+
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+ ```python
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+ !pip install -qU transformers accelerate
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+
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+ from transformers import AutoTokenizer
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+ import transformers
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+ import torch
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+
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+ model = "automerger/AlloyingotneoyExperiment24-7B"
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+ messages = [{"role": "user", "content": "What is a large language model?"}]
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+
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+ tokenizer = AutoTokenizer.from_pretrained(model)
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+ prompt = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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+ pipeline = transformers.pipeline(
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+ "text-generation",
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+ model=model,
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+ torch_dtype=torch.float16,
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+ device_map="auto",
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+ )
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+
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+ outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
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+ print(outputs[0]["generated_text"])
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+ ```