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@@ -34,11 +34,42 @@ The model performs exceptionally well on writing, explanation and discussion tas
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  - **Finetuned from:** [LeoLM/leo-hessianai-7b](https://huggingface.co/LeoLM/leo-hessianai-7b)
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  - **Model type:** Causal decoder-only transformer language model
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  - **Language:** English and German
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- - **Demo:** [Continuations for 250 random prompts (TGI, 4bit nf4 quantization)](https://open-assistant.github.io/oasst-model-eval/?f=https%3A%2F%2Fraw.githubusercontent.com%2FOpen-Assistant%2Foasst-model-eval%2Fmain%2Fsampling_reports%2Foasst-sft%2F2023-08-22_OpenAssistant_llama2-70b-oasst-sft-v10_sampling_noprefix2_nf4.json%0A)
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  - **License:** [LLAMA 2 COMMUNITY LICENSE AGREEMENT](https://huggingface.co/meta-llama/Llama-2-70b/raw/main/LICENSE.txt)
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  - **Contact:** [LAION Discord](https://discord.com/invite/eq3cAMZtCC) or [Björn Plüster](mailto:[email protected])
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  ## Prompting / Prompt Template
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  Prompt dialogue template (ChatML format):
 
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  - **Finetuned from:** [LeoLM/leo-hessianai-7b](https://huggingface.co/LeoLM/leo-hessianai-7b)
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  - **Model type:** Causal decoder-only transformer language model
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  - **Language:** English and German
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+ - **Demo:** [Web Demo]()
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  - **License:** [LLAMA 2 COMMUNITY LICENSE AGREEMENT](https://huggingface.co/meta-llama/Llama-2-70b/raw/main/LICENSE.txt)
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  - **Contact:** [LAION Discord](https://discord.com/invite/eq3cAMZtCC) or [Björn Plüster](mailto:[email protected])
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+ ## Use in 🤗Transformers
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+ If you want faster inference using flash-attention2, you need to install these dependencies:
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+ ```bash
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+ pip install packaging ninja
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+ pip install flash-attn==v2.1.1 --no-build-isolation
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+ pip install git+https://github.com/HazyResearch/[email protected]#subdirectory=csrc/rotary
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+ ```
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+ Then load the model in transformers:
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+ ```python
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+ from transformers import AutoModelForCausalLM, AutoTokenizer
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+ import torch
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+
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+ model = AutoModelForCausalLM.from_pretrained(
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+ "LeoLM/leo-hessianai-7b-chat",
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+ torch_dtype=torch.float16,
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+ trust_remote_code=True # True for flash-attn, else False
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+ )
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+ tokenizer = AutoTokenizer.from_pretrained("LeoLM/leo-hessianai-7b-chat")
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+
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+ system_prompt = """<|im_start|>system
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+ Dies ist eine Unterhaltung zwischen einem intelligenten, hilfsbereitem KI-Assistenten und einem Nutzer.
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+ Der Assistent gibt ausführliche, hilfreiche und ehrliche Antworten.<|im_end|>
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+
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+ """
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+
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+ prompt_format = "<|im_start|>user\n{prompt}<|im_end|>\n<|im_start|>assistant\n"
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+ prompt = "Erkläre mir wie die Fahrradwegesituation in Hamburg ist."
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+
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+ response, history = model.chat(tokenizer, prompt_format.format(prompt=prompt), history=None)
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+ ```
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+
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  ## Prompting / Prompt Template
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  Prompt dialogue template (ChatML format):