metadata
base_model: meta-llama/Meta-Llama-3-8B-Instruct
language:
- en
license: llama3
pipeline_tag: text-generation
tags:
- facebook
- meta
- pytorch
- llama
- llama-3
- llama-cpp
- gguf-my-repo
extra_gated_prompt: >-
### META LLAMA 3 COMMUNITY LICENSE AGREEMENT
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extra_gated_fields:
First Name: text
Last Name: text
Date of birth: date_picker
Country: country
Affiliation: text
geo: ip_location
By clicking Submit below I accept the terms of the license and acknowledge that the information I provide will be collected stored processed and shared in accordance with the Meta Privacy Policy: checkbox
extra_gated_description: >-
The information you provide will be collected, stored, processed and shared in
accordance with the [Meta Privacy
Policy](https://www.facebook.com/privacy/policy/).
extra_gated_button_content: Submit
widget:
- example_title: Hello
messages:
- role: user
content: Hey my name is Julien! How are you?
- example_title: Winter holidays
messages:
- role: system
content: >-
You are a helpful and honest assistant. Please, respond concisely and
truthfully.
- role: user
content: Can you recommend a good destination for Winter holidays?
- example_title: Programming assistant
messages:
- role: system
content: >-
You are a helpful and honest code and programming assistant. Please,
respond concisely and truthfully.
- role: user
content: Write a function that computes the nth fibonacci number.
inference:
parameters:
max_new_tokens: 300
stop:
- <|end_of_text|>
- <|eot_id|>
sdkramer10/Meta-Llama-3-8B-Instruct-Q4_K_M-GGUF
This model was converted to GGUF format from meta-llama/Meta-Llama-3-8B-Instruct using llama.cpp via the ggml.ai's GGUF-my-repo space.
Refer to the original model card for more details on the model.
Use with llama.cpp
Install llama.cpp through brew (works on Mac and Linux)
brew install llama.cpp
Invoke the llama.cpp server or the CLI.
CLI:
llama-cli --hf-repo sdkramer10/Meta-Llama-3-8B-Instruct-Q4_K_M-GGUF --hf-file meta-llama-3-8b-instruct-q4_k_m.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo sdkramer10/Meta-Llama-3-8B-Instruct-Q4_K_M-GGUF --hf-file meta-llama-3-8b-instruct-q4_k_m.gguf -c 2048
Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.
Step 1: Clone llama.cpp from GitHub.
git clone https://github.com/ggerganov/llama.cpp
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).
cd llama.cpp && LLAMA_CURL=1 make
Step 3: Run inference through the main binary.
./llama-cli --hf-repo sdkramer10/Meta-Llama-3-8B-Instruct-Q4_K_M-GGUF --hf-file meta-llama-3-8b-instruct-q4_k_m.gguf -p "The meaning to life and the universe is"
or
./llama-server --hf-repo sdkramer10/Meta-Llama-3-8B-Instruct-Q4_K_M-GGUF --hf-file meta-llama-3-8b-instruct-q4_k_m.gguf -c 2048