scholarly360
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Update README.md
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README.md
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@@ -51,26 +51,20 @@ Just like any ChatGPT equivalent model (For Contracts Domain)
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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[More Information Needed]
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### Downstream Use [optional]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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[More Information Needed]
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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[More Information Needed]
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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[More Information Needed]
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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>>> inputs = tokenizer(prompt, return_tensors="pt")
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>>> outputs = model.generate(**inputs)
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>>> print(tokenizer.batch_decode(outputs, skip_special_tokens=True))
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>>> ### Example
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>>> prompt = """ what is agreement date in 'This COLLABORATION AGREEMENT (Agreement) dated November 14, 2002, is made by and between ZZZ, INC., a Delaware corporation' """"
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>>> inputs = tokenizer(prompt, return_tensors="pt")
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>>> outputs = model.generate(**inputs)
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>>> print(tokenizer.batch_decode(outputs, skip_special_tokens=True))
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>>> ### Example 3
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>>> prompt = """ ### Instruction:
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what is agreement date
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### Input:
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This COLLABORATION AGREEMENT (Agreement) dated November 14, 2002, is made by and between ZZZ, INC., a Delaware corporation """"
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>>> inputs = tokenizer(prompt, return_tensors="pt")
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>>> outputs = model.generate(**inputs)
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>>> print(tokenizer.batch_decode(outputs, skip_special_tokens=True))
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@@ -115,7 +106,6 @@ This COLLABORATION AGREEMENT (Agreement) dated November 14, 2002, is made by and
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<!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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DataSet will be released soon for the community
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[More Information Needed]
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### Training Procedure
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<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
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### Downstream Use [optional]
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<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
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### Out-of-Scope Use
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<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
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## Bias, Risks, and Limitations
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<!-- This section is meant to convey both technical and sociotechnical limitations. -->
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### Recommendations
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<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
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>>> inputs = tokenizer(prompt, return_tensors="pt")
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>>> outputs = model.generate(**inputs)
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>>> print(tokenizer.batch_decode(outputs, skip_special_tokens=True))
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>>> ### Example 2
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>>> prompt = """ what is agreement date in 'This COLLABORATION AGREEMENT (Agreement) dated November 14, 2002, is made by and between ZZZ, INC., a Delaware corporation' """"
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>>> inputs = tokenizer(prompt, return_tensors="pt")
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>>> outputs = model.generate(**inputs)
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>>> print(tokenizer.batch_decode(outputs, skip_special_tokens=True))
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>>> ### Example 3
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>>> prompt = """ ### Instruction: \n\n what is agreement date ### Input: \n\n This COLLABORATION AGREEMENT (Agreement) dated November 14, 2002, is made by and between ZZZ, INC., a Delaware corporation """"
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>>> inputs = tokenizer(prompt, return_tensors="pt")
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>>> outputs = model.generate(**inputs)
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>>> print(tokenizer.batch_decode(outputs, skip_special_tokens=True))
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<!-- This should link to a Data Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
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DataSet will be released soon for the community
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### Training Procedure
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