Text Generation
GGUF
English
fireplace
fireplace-2
valiant
valiant-labs
llama
llama-3.1
llama-3.1-instruct
llama-3.1-instruct-8b
llama-3
llama-3-instruct
llama-3-instruct-8b
8b
function-calling
sql
database
data-visualization
matplotlib
json
conversational
chat
instruct
llama-cpp
gguf-my-repo
Inference Endpoints
Upload README.md with huggingface_hub
Browse files
README.md
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---
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base_model: ValiantLabs/Llama3.1-8B-Fireplace2
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language:
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- en
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license: llama3.1
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pipeline_tag: text-generation
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tags:
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- fireplace
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- fireplace-2
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- valiant
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- valiant-labs
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- llama
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- llama-3.1
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- llama-3.1-instruct
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- llama-3.1-instruct-8b
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- llama-3
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- llama-3-instruct
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- llama-3-instruct-8b
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- 8b
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- function-calling
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- sql
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- database
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- data-visualization
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- matplotlib
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- json
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- conversational
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- chat
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- instruct
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- llama-cpp
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- gguf-my-repo
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model_type: llama
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---
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# mudler/Llama3.1-8B-Fireplace2-Q4_K_M-GGUF
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This model was converted to GGUF format from [`ValiantLabs/Llama3.1-8B-Fireplace2`](https://huggingface.co/ValiantLabs/Llama3.1-8B-Fireplace2) 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/ValiantLabs/Llama3.1-8B-Fireplace2) 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 mudler/Llama3.1-8B-Fireplace2-Q4_K_M-GGUF --hf-file llama3.1-8b-fireplace2-q4_k_m.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 mudler/Llama3.1-8B-Fireplace2-Q4_K_M-GGUF --hf-file llama3.1-8b-fireplace2-q4_k_m.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 mudler/Llama3.1-8B-Fireplace2-Q4_K_M-GGUF --hf-file llama3.1-8b-fireplace2-q4_k_m.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 mudler/Llama3.1-8B-Fireplace2-Q4_K_M-GGUF --hf-file llama3.1-8b-fireplace2-q4_k_m.gguf -c 2048
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```
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