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Update README.md

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@@ -143,7 +143,7 @@ The following clients/libraries will automatically download models for you, prov
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  ### In `text-generation-webui`
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- Under Download Model, you can enter the model repo: TheBloke/Llama-2-7B-GGUF and below it, a specific filename to download, such as: llama-2-7b.q4_K_M.gguf.
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  Then click Download.
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@@ -158,7 +158,7 @@ pip3 install huggingface-hub>=0.17.1
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  Then you can download any individual model file to the current directory, at high speed, with a command like this:
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  ```shell
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- huggingface-cli download TheBloke/Llama-2-7B-GGUF llama-2-7b.q4_K_M.gguf --local-dir . --local-dir-use-symlinks False
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  ```
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  <details>
@@ -181,7 +181,7 @@ pip3 install hf_transfer
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  And set environment variable `HF_HUB_ENABLE_HF_TRANSFER` to `1`:
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  ```shell
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- HUGGINGFACE_HUB_ENABLE_HF_TRANSFER=1 huggingface-cli download TheBloke/Llama-2-7B-GGUF llama-2-7b.q4_K_M.gguf --local-dir . --local-dir-use-symlinks False
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  ```
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  Windows CLI users: Use `set HUGGINGFACE_HUB_ENABLE_HF_TRANSFER=1` before running the download command.
@@ -194,7 +194,7 @@ Windows CLI users: Use `set HUGGINGFACE_HUB_ENABLE_HF_TRANSFER=1` before running
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  Make sure you are using `llama.cpp` from commit [d0cee0d36d5be95a0d9088b674dbb27354107221](https://github.com/ggerganov/llama.cpp/commit/d0cee0d36d5be95a0d9088b674dbb27354107221) or later.
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  ```shell
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- ./main -ngl 32 -m llama-2-7b.q4_K_M.gguf --color -c 4096 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "{prompt}"
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  ```
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  Change `-ngl 32` to the number of layers to offload to GPU. Remove it if you don't have GPU acceleration.
@@ -234,7 +234,7 @@ CT_METAL=1 pip install ctransformers>=0.2.24 --no-binary ctransformers
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  from ctransformers import AutoModelForCausalLM
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  # Set gpu_layers to the number of layers to offload to GPU. Set to 0 if no GPU acceleration is available on your system.
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- llm = AutoModelForCausalLM.from_pretrained("TheBloke/Llama-2-7B-GGUF", model_file="llama-2-7b.q4_K_M.gguf", model_type="llama", gpu_layers=50)
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  print(llm("AI is going to"))
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  ```
 
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  ### In `text-generation-webui`
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+ Under Download Model, you can enter the model repo: TheBloke/Llama-2-7B-GGUF and below it, a specific filename to download, such as: llama-2-7b.Q4_K_M.gguf.
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  Then click Download.
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  Then you can download any individual model file to the current directory, at high speed, with a command like this:
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  ```shell
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+ huggingface-cli download TheBloke/Llama-2-7B-GGUF llama-2-7b.Q4_K_M.gguf --local-dir . --local-dir-use-symlinks False
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  ```
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  <details>
 
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  And set environment variable `HF_HUB_ENABLE_HF_TRANSFER` to `1`:
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  ```shell
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+ HUGGINGFACE_HUB_ENABLE_HF_TRANSFER=1 huggingface-cli download TheBloke/Llama-2-7B-GGUF llama-2-7b.Q4_K_M.gguf --local-dir . --local-dir-use-symlinks False
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  ```
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  Windows CLI users: Use `set HUGGINGFACE_HUB_ENABLE_HF_TRANSFER=1` before running the download command.
 
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  Make sure you are using `llama.cpp` from commit [d0cee0d36d5be95a0d9088b674dbb27354107221](https://github.com/ggerganov/llama.cpp/commit/d0cee0d36d5be95a0d9088b674dbb27354107221) or later.
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  ```shell
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+ ./main -ngl 32 -m llama-2-7b.Q4_K_M.gguf --color -c 4096 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "{prompt}"
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  ```
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  Change `-ngl 32` to the number of layers to offload to GPU. Remove it if you don't have GPU acceleration.
 
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  from ctransformers import AutoModelForCausalLM
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  # Set gpu_layers to the number of layers to offload to GPU. Set to 0 if no GPU acceleration is available on your system.
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+ llm = AutoModelForCausalLM.from_pretrained("TheBloke/Llama-2-7B-GGUF", model_file="llama-2-7b.Q4_K_M.gguf", model_type="llama", gpu_layers=50)
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  print(llm("AI is going to"))
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  ```