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README.md
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---
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base_model: hpcgroup/hpc-coder-v2-1.3b
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datasets:
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- hpcgroup/hpc-instruct
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- ise-uiuc/Magicoder-OSS-Instruct-75K
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- nickrosh/Evol-Instruct-Code-80k-v1
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language:
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- en
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library_name: transformers
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pipeline_tag: text-generation
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tags:
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- code
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- hpc
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- gguf-my-repo
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---
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#
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This
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Refer to the [original model card](https://huggingface.co/hpcgroup/hpc-coder-v2-1.3b) for more details on the model.
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## Use with llama.cpp
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```bash
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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 daniellnichols/hpc-coder-v2-1.3b-Q8_0-GGUF --hf-file hpc-coder-v2-1.3b-q8_0.gguf -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 daniellnichols/hpc-coder-v2-1.3b-Q8_0-GGUF --hf-file hpc-coder-v2-1.3b-q8_0.gguf -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: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux).
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```
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cd llama.cpp && LLAMA_CURL=1 make
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```
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Step 3: Run inference through the main binary.
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```
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./llama-cli --hf-repo daniellnichols/hpc-coder-v2-1.3b-Q8_0-GGUF --hf-file hpc-coder-v2-1.3b-q8_0.gguf -p "The meaning to life and the universe is"
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```
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or
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```
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./llama-server --hf-repo daniellnichols/hpc-coder-v2-1.3b-Q8_0-GGUF --hf-file hpc-coder-v2-1.3b-q8_0.gguf -c 2048
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```
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---
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base_model: hpcgroup/hpc-coder-v2-1.3b
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library_name: transformers
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tags:
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- code
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- hpc
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- gguf-my-repo
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# HPC-Coder-v2-1.3b-Q8_0-GGUF
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This is the [HPC-Coder-v2-6.7b](https://huggingface.co/hpcgroup/hpc-coder-v2-1.3b) model with 8 bit quantized weights in the GGUF format that can be used with llama.cpp.
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Refer to the [original model card](https://huggingface.co/hpcgroup/hpc-coder-v2-1.3b) for more details on the model.
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## Use with llama.cpp
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See the [llama.cpp repo](https://github.com/ggerganov/llama.cpp) for installation instructions.
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You can then use the model as:
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```bash
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llama-cli --hf-repo hpcgroup/hpc-coder-v2-1.3b-Q8_0-GGUF --hf-file hpc-coder-v2-1.3b-q8_0.gguf -r "Below is an instruction that describes a task. Write a response that appropriately completes the request.\n\n### Instruction:" --in-prefix "\n" --in-suffix "\n### Response:\n" -c 8096 -p "your prompt here"
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```
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