readme : update gpt4all instructions

README.md

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