MaziyarPanahi
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Update README.md (#2)
Browse files- Update README.md (7f63b892a621e3a5ce7e7145dd79157ee56a7ef7)
README.md
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@@ -117,7 +117,7 @@ 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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HF_HUB_ENABLE_HF_TRANSFER=1 huggingface-cli download MaziyarPanahi/Experiment26-7B-GGUF Experiment26-7B
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```
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Windows Command Line users: You can set the environment variable by running `set HF_HUB_ENABLE_HF_TRANSFER=1` before the download command.
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Make sure you are using `llama.cpp` from commit [d0cee0d](https://github.com/ggerganov/llama.cpp/commit/d0cee0d36d5be95a0d9088b674dbb27354107221) or later.
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```shell
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./main -ngl 35 -m Experiment26-7B
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{system_message}<|im_end|>
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<|im_start|>user
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{prompt}<|im_end|>
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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 = Llama(
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model_path="./Experiment26-7B
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n_ctx=32768, # The max sequence length to use - note that longer sequence lengths require much more resources
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n_threads=8, # The number of CPU threads to use, tailor to your system and the resulting performance
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n_gpu_layers=35 # The number of layers to offload to GPU, if you have GPU acceleration available
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# Chat Completion API
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llm = Llama(model_path="./Experiment26-7B
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llm.create_chat_completion(
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messages = [
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{"role": "system", "content": "You are a story writing assistant."},
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And set environment variable `HF_HUB_ENABLE_HF_TRANSFER` to `1`:
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```shell
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HF_HUB_ENABLE_HF_TRANSFER=1 huggingface-cli download MaziyarPanahi/Experiment26-7B-GGUF Experiment26-7B.Q4_K_M.gguf --local-dir . --local-dir-use-symlinks False
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```
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Windows Command Line users: You can set the environment variable by running `set HF_HUB_ENABLE_HF_TRANSFER=1` before the download command.
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Make sure you are using `llama.cpp` from commit [d0cee0d](https://github.com/ggerganov/llama.cpp/commit/d0cee0d36d5be95a0d9088b674dbb27354107221) or later.
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```shell
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./main -ngl 35 -m Experiment26-7B.Q4_K_M.gguf --color -c 32768 --temp 0.7 --repeat_penalty 1.1 -n -1 -p "<|im_start|>system
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{system_message}<|im_end|>
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<|im_start|>user
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{prompt}<|im_end|>
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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 = Llama(
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model_path="./Experiment26-7B.Q4_K_M.gguf", # Download the model file first
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n_ctx=32768, # The max sequence length to use - note that longer sequence lengths require much more resources
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n_threads=8, # The number of CPU threads to use, tailor to your system and the resulting performance
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n_gpu_layers=35 # The number of layers to offload to GPU, if you have GPU acceleration available
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# Chat Completion API
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llm = Llama(model_path="./Experiment26-7B.Q4_K_M.gguf", chat_format="llama-2") # Set chat_format according to the model you are using
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llm.create_chat_completion(
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messages = [
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{"role": "system", "content": "You are a story writing assistant."},
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