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README.md
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@@ -20,19 +20,20 @@ We evaluated model_51 on a wide range of tasks using [Language Model Evaluation
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Here are the results on metrics used by [HuggingFaceH4 Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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|**Task**|**
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##
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Here is the prompt format
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```
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### System:
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```
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Below shows a code example on how to use this model
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```python
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
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tokenizer = AutoTokenizer.from_pretrained("
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model = AutoModelForCausalLM.from_pretrained(
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torch_dtype=torch.float16,
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low_cpu_mem_usage=True,
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device_map="auto"
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)
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Here are the results on metrics used by [HuggingFaceH4 Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard)
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|**Task**|**Value**|
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|*ARC*|0.6843|
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|*HellaSwag*|0.8671|
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|*MMLU*|0.6931|
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|*TruthfulQA*|0.5718|
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|*Winogrande*|0.8177|
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|*GSM8K*|0.3237|
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|*DROP*|0.5843|
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|**Total Average**|**0.6488**|
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### Prompt Foramt
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```
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### System:
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```
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#### OobaBooga Instructions:
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This model required upto 45GB GPU VRAM in 4bit so it can be loaded directly on Single RTX 6000/L40/A40/A100/H100 GPU or Double RTX 4090/L4/A10/RTX 3090/RTX A5000
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So, if you have access to Machine with 45GB GPU VRAM and have installed [OobaBooga Web UI](https://github.com/oobabooga/text-generation-webui) on it.
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You can just download this model by using HF repo link directly on OobaBooga Web UI "Model" Tab/Page & Just use **load-in-4bit** option in it.
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After that go to Default Tab/Page on OobaBooga Web UI and **copy paste above prompt format into Input** and Enjoy!
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<br>
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#### Code Instructions:
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Below shows a code example on how to use this model
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```python
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import torch
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from transformers import AutoModelForCausalLM, AutoTokenizer, pipeline
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tokenizer = AutoTokenizer.from_pretrained("pankajmathur/model_51")
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model = AutoModelForCausalLM.from_pretrained(
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"pankajmathur/model_51",
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torch_dtype=torch.float16,
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load_in_4bit=True,
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low_cpu_mem_usage=True,
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device_map="auto"
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)
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