Text Generation
Transformers
PyTorch
English
gpt_neox
text-generation-inference
Inference Endpoints
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@@ -29,15 +29,15 @@ inference:
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  max_new_tokens: 128
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  ---
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- # RedPajama-INCITE-Instruct-7B-v0.1
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- RedPajama-INCITE-Instruct-7B-v0.1 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-Base-7B-v0.1](https://huggingface.co/togethercomputer/RedPajama-INCITE-Base-7B-v0.1)
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- - Instruction-tuned Version: [RedPajama-INCITE-Instruct-7B-v0.1](https://huggingface.co/togethercomputer/RedPajama-INCITE-Instruct-7B-v0.1)
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- - Chat Version: [RedPajama-INCITE-Chat-7B-v0.1](https://huggingface.co/togethercomputer/RedPajama-INCITE-Chat-7B-v0.1)
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  ## Model Details
@@ -66,8 +66,8 @@ MIN_TRANSFORMERS_VERSION = '4.25.1'
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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-Instruct-7B-v0.1")
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- model = AutoModelForCausalLM.from_pretrained("togethercomputer/RedPajama-INCITE-Instruct-7B-v0.1", 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:"
@@ -108,8 +108,8 @@ MIN_TRANSFORMERS_VERSION = '4.25.1'
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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-Instruct-7B-v0.1")
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- model = AutoModelForCausalLM.from_pretrained("togethercomputer/RedPajama-INCITE-Instruct-7B-v0.1", 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:"
@@ -139,8 +139,8 @@ MIN_TRANSFORMERS_VERSION = '4.25.1'
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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-Instruct-7B-v0.1")
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- model = AutoModelForCausalLM.from_pretrained("togethercomputer/RedPajama-INCITE-Instruct-7B-v0.1", 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)
@@ -171,13 +171,13 @@ It is the responsibility of the end user to ensure that the model is used in a r
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  #### Out-of-Scope Use
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- RedPajama-INCITE-Instruct-7B-v0.1 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-Instruct-7B-v0.1 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:
@@ -194,7 +194,7 @@ Using the model to generate content that is cruel to individuals is a misuse of
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  ## Limitations
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- RedPajama-INCITE-Instruct-7B-v0.1, 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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@@ -209,7 +209,7 @@ Please refer to [togethercomputer/RedPajama-Data-1T](https://huggingface.co/data
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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:** 131M 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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  ---
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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.
175
  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.
176
  It is important to consider the limitations of the model and to only use it for its intended purpose.
177
 
178
  #### Misuse and Malicious Use
179
 
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+ RedPajama-INCITE-7B-Instruct is designed for language modeling.
181
  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.
198
  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.
199
  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