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jeevavijay10
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37198ae
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8dd83e6
Update app.py
Browse files
app.py
CHANGED
@@ -9,19 +9,23 @@ tokenizer = AutoTokenizer.from_pretrained(model_id)
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def chat(question):
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prompt = f"### Instruction: {question}\n### Response:"
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inputs = tokenizer(prompt, return_tensors="pt")
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output = model.generate(inputs["input_ids"]
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response = tokenizer.decode(output[0].tolist(), skip_special_tokens=True)
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print(response)
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return response
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iface = gr.Interface(fn=chat,
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inputs=gr.inputs.Textbox(label="Enter your text"),
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outputs="text",
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title="Chat with
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# index = construct_index("docs")
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iface.launch()
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def chat(question):
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prompt = f"### Instruction: {question}\n### Response:"
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inputs = tokenizer(prompt, return_tensors="pt")
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output = model.generate(inputs["input_ids"])
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response = tokenizer.decode(output[0].tolist())
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print(response)
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return response
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iface = gr.Interface(fn=chat,
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inputs=gr.inputs.Textbox(label="Enter your text"),
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outputs="text",
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title="Chat with Raven")
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# index = construct_index("docs")
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iface.launch()
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### Instruction: How do I train the RWKV on specific data?
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### Response: To train the RWKV on specific data, you can use the `train_rwkv`
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# function from the `sklearn.model_selection` module.
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# This function takes a list of data points as input and returns a list of predictions for each data point. You can then use this list of predictions to train the RWKV on your specific data.
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