Text Generation
Transformers
PyTorch
English
gpt_neox
text-generation-inference
Inference Endpoints
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@@ -4,9 +4,9 @@ language:
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  - en
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  ---
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- # RedPajama-Instruct-INCITE-6.9B
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- RedPajama-Instruct-INCITE-6.9B-v1, is a large transformer-based language model developed by Together Computer and trained on the RedPajama-Data-1T dataset.
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  ## Model Details
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  - **Developed by**: Together Computer.
@@ -34,8 +34,8 @@ 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-Instruct-INCITE-6.9B-v1")
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- model = AutoModelForCausalLM.from_pretrained("togethercomputer/RedPajama-Instruct-INCITE-6.9B-v1", 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:"
@@ -76,8 +76,8 @@ 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-Instruct-INCITE-6.9B-v1")
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- model = AutoModelForCausalLM.from_pretrained("togethercomputer/RedPajama-Instruct-INCITE-6.9B-v1", 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:"
@@ -107,8 +107,8 @@ 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-Instruct-INCITE-6.9B-v1")
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- model = AutoModelForCausalLM.from_pretrained("togethercomputer/RedPajama-Instruct-INCITE-6.9B-v1", 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)
@@ -147,13 +147,13 @@ 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-Instruct-INCITE-6.9B 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-Instruct-INCITE-6.9B 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 OpenChatKit community 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:
@@ -170,7 +170,7 @@ 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-Instruct-INCITE-6.9B, 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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  - en
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  ---
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+ # RedPajama-INCITE-Instruct-7B-v0.1
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+ RedPajama-INCITE-Instruct-7B-v0.1, is a large transformer-based language model developed by Together Computer and trained on the RedPajama-Data-1T dataset.
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  ## Model Details
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  - **Developed by**: Together Computer.
 
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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:"
 
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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:"
 
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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)
 
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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.
151
  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.
152
  It is important to consider the limitations of the model and to only use it for its intended purpose.
153
 
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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 OpenChatKit community project.
158
 
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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-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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