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README.md
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# RedPajama-INCITE-
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RedPajama-INCITE-
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The model was fine-tuned for few-shot applications on the data of [GPT-JT](https://huggingface.co/togethercomputer/GPT-JT-6B-v1), with exclusion of tasks that overlap with the HELM core scenarios.
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- Base Model: [RedPajama-INCITE-
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- Instruction-tuned Version: [RedPajama-INCITE-
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- Chat Version: [RedPajama-INCITE-
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## Model Details
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assert transformers.__version__ >= MIN_TRANSFORMERS_VERSION, f'Please upgrade transformers to version {MIN_TRANSFORMERS_VERSION} or higher.'
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# init
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tokenizer = AutoTokenizer.from_pretrained("togethercomputer/RedPajama-INCITE-
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model = AutoModelForCausalLM.from_pretrained("togethercomputer/RedPajama-INCITE-
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model = model.to('cuda:0')
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# infer
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prompt = "Q: The capital of France is?\nA:"
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assert transformers.__version__ >= MIN_TRANSFORMERS_VERSION, f'Please upgrade transformers to version {MIN_TRANSFORMERS_VERSION} or higher.'
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# init
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tokenizer = AutoTokenizer.from_pretrained("togethercomputer/RedPajama-INCITE-
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model = AutoModelForCausalLM.from_pretrained("togethercomputer/RedPajama-INCITE-
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# infer
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prompt = "Q: The capital of France is?\nA:"
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assert transformers.__version__ >= MIN_TRANSFORMERS_VERSION, f'Please upgrade transformers to version {MIN_TRANSFORMERS_VERSION} or higher.'
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# init
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tokenizer = AutoTokenizer.from_pretrained("togethercomputer/RedPajama-INCITE-
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model = AutoModelForCausalLM.from_pretrained("togethercomputer/RedPajama-INCITE-
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# infer
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prompt = "Q: The capital of France is?\nA:"
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inputs = tokenizer(prompt, return_tensors='pt').to(model.device)
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#### Out-of-Scope Use
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RedPajama-INCITE-
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For example, it may not be suitable for use in safety-critical applications or for making decisions that have a significant impact on individuals or society.
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It is important to consider the limitations of the model and to only use it for its intended purpose.
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#### Misuse and Malicious Use
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RedPajama-INCITE-
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Misuse of the model, such as using it to engage in illegal or unethical activities, is strictly prohibited and goes against the principles of the project.
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Using the model to generate content that is cruel to individuals is a misuse of this model. This includes, but is not limited to:
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## Limitations
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RedPajama-INCITE-
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For example, the model may not always provide accurate or relevant answers, particularly for questions that are complex, ambiguous, or outside of its training data.
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We therefore welcome contributions from individuals and organizations, and encourage collaboration towards creating a more robust and inclusive chatbot.
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- **Hardware:** 8 A100
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- **Optimizer:** Adam
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- **Gradient Accumulations**: 1
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- **Num of Tokens:**
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- **Learning rate:** 1e-5
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## Community
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max_new_tokens: 128
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# RedPajama-INCITE-7B-Instruct
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RedPajama-INCITE-7B-Instruct was developed by Together and leaders from the open-source AI community including Ontocord.ai, ETH DS3Lab, AAI CERC, Université de Montréal, MILA - Québec AI Institute, Stanford Center for Research on Foundation Models (CRFM), Stanford Hazy Research research group and LAION.
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The model was fine-tuned for few-shot applications on the data of [GPT-JT](https://huggingface.co/togethercomputer/GPT-JT-6B-v1), with exclusion of tasks that overlap with the HELM core scenarios.
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- Base Model: [RedPajama-INCITE-7B-Base](https://huggingface.co/togethercomputer/RedPajama-INCITE-7B-Base)
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- Instruction-tuned Version: [RedPajama-INCITE-7B-Instruct](https://huggingface.co/togethercomputer/RedPajama-INCITE-7B-Instruct)
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- Chat Version: [RedPajama-INCITE-7B-Chat](https://huggingface.co/togethercomputer/RedPajama-INCITE-7B-Chat)
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## Model Details
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assert transformers.__version__ >= MIN_TRANSFORMERS_VERSION, f'Please upgrade transformers to version {MIN_TRANSFORMERS_VERSION} or higher.'
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# init
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tokenizer = AutoTokenizer.from_pretrained("togethercomputer/RedPajama-INCITE-7B-Instruct")
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model = AutoModelForCausalLM.from_pretrained("togethercomputer/RedPajama-INCITE-7B-Instruct", torch_dtype=torch.float16)
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model = model.to('cuda:0')
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# infer
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prompt = "Q: The capital of France is?\nA:"
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assert transformers.__version__ >= MIN_TRANSFORMERS_VERSION, f'Please upgrade transformers to version {MIN_TRANSFORMERS_VERSION} or higher.'
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# init
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tokenizer = AutoTokenizer.from_pretrained("togethercomputer/RedPajama-INCITE-7B-Instruct")
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model = AutoModelForCausalLM.from_pretrained("togethercomputer/RedPajama-INCITE-7B-Instruct", device_map='auto', torch_dtype=torch.float16, load_in_8bit=True)
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# infer
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prompt = "Q: The capital of France is?\nA:"
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assert transformers.__version__ >= MIN_TRANSFORMERS_VERSION, f'Please upgrade transformers to version {MIN_TRANSFORMERS_VERSION} or higher.'
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# init
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tokenizer = AutoTokenizer.from_pretrained("togethercomputer/RedPajama-INCITE-7B-Instruct")
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model = AutoModelForCausalLM.from_pretrained("togethercomputer/RedPajama-INCITE-7B-Instruct", torch_dtype=torch.bfloat16)
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# infer
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prompt = "Q: The capital of France is?\nA:"
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inputs = tokenizer(prompt, return_tensors='pt').to(model.device)
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#### Out-of-Scope Use
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RedPajama-INCITE-7B-Instruct is a language model and may not perform well for other use cases outside of its intended scope.
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For example, it may not be suitable for use in safety-critical applications or for making decisions that have a significant impact on individuals or society.
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It is important to consider the limitations of the model and to only use it for its intended purpose.
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#### Misuse and Malicious Use
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RedPajama-INCITE-7B-Instruct is designed for language modeling.
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Misuse of the model, such as using it to engage in illegal or unethical activities, is strictly prohibited and goes against the principles of the project.
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Using the model to generate content that is cruel to individuals is a misuse of this model. This includes, but is not limited to:
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## Limitations
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RedPajama-INCITE-7B-Instruct, like other language models, has limitations that should be taken into consideration.
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For example, the model may not always provide accurate or relevant answers, particularly for questions that are complex, ambiguous, or outside of its training data.
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We therefore welcome contributions from individuals and organizations, and encourage collaboration towards creating a more robust and inclusive chatbot.
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- **Hardware:** 8 A100
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- **Optimizer:** Adam
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- **Gradient Accumulations**: 1
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- **Num of Tokens:** 1B tokens
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- **Learning rate:** 1e-5
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## Community
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