From 678283ea8d0ed4f40aaf7a0e5708ccc6812fc6b4 Mon Sep 17 00:00:00 2001
From: oobabooga <112222186+oobabooga@users.noreply.github.com>
Date: Fri, 17 Mar 2023 11:49:31 -0300
Subject: [PATCH] Updated Home (markdown)

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 Using-LoRAs.md | 54 ++++++++++++++++++++++++++++++++++++++++++++++++++
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-Welcome to the text-generation-webui wiki!
diff --git a/Using-LoRAs.md b/Using-LoRAs.md
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+Based on https://github.com/tloen/alpaca-lora/
+
+Probably not the best way to do it. WIP. Suggestions are welcome.
+
+## Instructions
+1. Re-install the requirements
+
+```
+pip install -r requirements.txt
+```
+
+2. Download the LoRA
+
+```
+python download-model.py tloen/alpaca-lora-7b
+```
+
+3. Load llama-7b in 8-bit mode (it only seems to work in 8-bit mode, don't ask me why)
+
+```
+python server.py --model llama-7b --load-in-8bit
+```
+
+4. Select the LoRA in the Parameters tab.
+
+## Prompt
+For this particular LoRA, apparently the prompt must be formatted like this:
+
+```
+Below is an instruction that describes a task. Write a response that appropriately completes the request.
+### Instruction:
+Write a Python script that generates text using the transformers library.
+### Response:
+```
+
+Sample output:
+
+```
+Below is an instruction that describes a task. Write a response that appropriately completes the request.
+### Instruction:
+Write a Python script that generates text using the transformers library.
+### Response:
+
+import transformers
+from transformers import AutoTokenizer, AutoModelForCausalLM
+tokenizer = AutoTokenizer.from_pretrained("bert-base-uncased")
+model = AutoModelForCausalLM.from_pretrained("bert-base-uncased")
+texts = ["Hello world", "How are you"]
+for sentence in texts:
+sentence = tokenizer(sentence)
+print(f"Generated {len(sentence)} tokens from '{sentence}'")
+output = model(sentences=sentence).predict()
+print(f"Predicted {len(output)} tokens for '{sentence}':\n{output}")
+```
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