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@@ -275,18 +275,19 @@ cadaver, cauliflower, cabbage (vegetable), catalpa (tree) and Cailleach.
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### Using [GPT4All](https://github.com/nomic-ai/gpt4all)
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### Using [GPT4All](https://github.com/nomic-ai/gpt4all)
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-- Obtain the `gpt4all-lora-quantized.bin` model
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-- It is distributed in the old `ggml` format, which is now obsoleted
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-- You have to convert it to the new format using [./convert-gpt4all-to-ggml.py](./convert-gpt4all-to-ggml.py). You may also need to
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-convert the model from the old format to the new format with [./migrate-ggml-2023-03-30-pr613.py](./migrate-ggml-2023-03-30-pr613.py):
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-
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- ```bash
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- python3 convert-gpt4all-to-ggml.py models/gpt4all-7B/gpt4all-lora-quantized.bin ./models/tokenizer.model
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- python3 migrate-ggml-2023-03-30-pr613.py models/gpt4all-7B/gpt4all-lora-quantized.bin models/gpt4all-7B/gpt4all-lora-quantized-new.bin
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- ```
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-
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-- You can now use the newly generated `gpt4all-lora-quantized-new.bin` model in exactly the same way as all other models
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-- The original model is saved in the same folder with a suffix `.orig`
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+- Obtain the `tokenizer.model` file from LLaMA model and put it to `models`
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+- Obtain the `added_tokens.json` file from Alpaca model and put it to `models`
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+- Obtain the `gpt4all-lora-quantized.bin` file from GPT4All model and put it to `models/gpt4all-7B`
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+- It is distributed in the old `ggml` format which is now obsoleted
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+- You have to convert it to the new format using `convert.py`:
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+
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+```bash
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+python3 convert.py models/gpt4all-7B/gpt4all-lora-quantized.bin
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+```
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+
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+- You can now use the newly generated `models/gpt4all-7B/ggml-model-q4_0.bin` model in exactly the same way as all other models
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+
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+- The newer GPT4All-J model is not yet supported!
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### Obtaining and verifying the Facebook LLaMA original model and Stanford Alpaca model data
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### Obtaining and verifying the Facebook LLaMA original model and Stanford Alpaca model data
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