Spaces:
Running
on
A10G
Running
on
A10G
Update app.py
Browse filesllama.cpp no longer supports building via `make`, update to CMake instructions in generated model card..
app.py
CHANGED
@@ -228,45 +228,51 @@ def process_model(model_id, q_method, use_imatrix, imatrix_q_method, private_rep
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# {new_repo_id}
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This model was converted to GGUF format from [`{model_id}`](https://huggingface.co/{model_id}) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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Refer to the [original model card](https://huggingface.co/{model_id}) for more details on the model.
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## Use with llama.cpp
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Install llama.cpp through brew (works on Mac and Linux)
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```bash
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brew install llama.cpp
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```
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Invoke the llama.cpp server or the CLI.
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### CLI:
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```bash
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llama-cli --hf-repo {new_repo_id} --hf-file {quantized_gguf_name} -p "The meaning to life and the universe is"
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```
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### Server:
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```bash
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llama-server --hf-repo {new_repo_id} --hf-file {quantized_gguf_name} -c 2048
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```
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Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
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Step 1: Clone llama.cpp from GitHub.
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```
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git clone https://github.com/ggerganov/llama.cpp
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```
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Step 2:
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```
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```
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```
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```
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```
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```
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"""
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)
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# {new_repo_id}
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This model was converted to GGUF format from [`{model_id}`](https://huggingface.co/{model_id}) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
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Refer to the [original model card](https://huggingface.co/{model_id}) for more details on the model.
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+
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## Use with llama.cpp
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Install llama.cpp through brew (works on Mac and Linux)
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```bash
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brew install llama.cpp
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```
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Invoke the llama.cpp server or the CLI.
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+
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### CLI:
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```bash
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llama-cli --hf-repo {new_repo_id} --hf-file {quantized_gguf_name} -p "The meaning to life and the universe is"
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```
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+
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### Server:
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```bash
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llama-server --hf-repo {new_repo_id} --hf-file {quantized_gguf_name} -c 2048
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```
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+
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Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well.
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Step 1: Clone llama.cpp from GitHub.
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```bash
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git clone https://github.com/ggerganov/llama.cpp
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cd llama.cpp
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```
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Step 2: Build using CMake. For CPU-only use:
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```bash
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cmake -B build
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cmake --build build --config Release
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```
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For CUDA support on Linux/Windows:
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```bash
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cmake -B build -DGGML_CUDA=ON
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cmake --build build --config Release
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```
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Step 3: Run inference through the binary (from the llama.cpp folder):
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```bash
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./build/bin/llama-cli --hf-repo {new_repo_id} --hf-file {quantized_gguf_name} -p "The meaning to life and the universe is"
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```
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or
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```bash
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./build/bin/llama-server --hf-repo {new_repo_id} --hf-file {quantized_gguf_name} -c 2048
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```
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"""
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)
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