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---
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base_model: prithivMLmods/Pictor-1338-QwenP-1.5B
language:
- en
library_name: transformers
license: apache-2.0
pipeline_tag: text-generation
tags:
- text-generation-inference
- RL
- Code
- Math
- llama-cpp
- gguf-my-repo
---
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# prithivMLmods/Pictor-1338-QwenP-1.5B-Q8_0-GGUF
This model was converted to GGUF format from [`prithivMLmods/Pictor-1338-QwenP-1.5B`](https://huggingface.co/prithivMLmods/Pictor-1338-QwenP-1.5B) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space.
Refer to the [original model card](https://huggingface.co/prithivMLmods/Pictor-1338-QwenP-1.5B) for more details on the model.
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## Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)
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```bash
brew install llama.cpp
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```
Invoke the llama.cpp server or the CLI.
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### CLI:
```bash
llama-cli --hf-repo prithivMLmods/Pictor-1338-QwenP-1.5B-Q8_0-GGUF --hf-file pictor-1338-qwenp-1.5b-q8_0.gguf -p "The meaning to life and the universe is"
```
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### Server:
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```bash
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llama-server --hf-repo prithivMLmods/Pictor-1338-QwenP-1.5B-Q8_0-GGUF --hf-file pictor-1338-qwenp-1.5b-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.
Step 1: Clone llama.cpp from GitHub.
```
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.
```
./llama-cli --hf-repo prithivMLmods/Pictor-1338-QwenP-1.5B-Q8_0-GGUF --hf-file pictor-1338-qwenp-1.5b-q8_0.gguf -p "The meaning to life and the universe is"
```
or
```
./llama-server --hf-repo prithivMLmods/Pictor-1338-QwenP-1.5B-Q8_0-GGUF --hf-file pictor-1338-qwenp-1.5b-q8_0.gguf -c 2048
```