metadata
language:
- en
license: apache-2.0
library_name: transformers
tags:
- transformers
- llama-cpp
- gguf-my-repo
base_model: openlm-research/open_llama_3b
datasets:
- mwitiderrick/AlpacaCode
inference: true
model_type: llama
prompt_template: |
### Instruction:\n
{prompt}
### Response:
created_by: mwitiderrick
pipeline_tag: text-generation
model-index:
- name: mwitiderrick/open_llama_3b_instruct_v_0.2
results:
- task:
type: text-generation
dataset:
name: hellaswag
type: hellaswag
metrics:
- type: hellaswag (0-Shot)
value: 0.6581
name: hellaswag(0-Shot)
- task:
type: text-generation
dataset:
name: winogrande
type: winogrande
metrics:
- type: winogrande (0-Shot)
value: 0.6267
name: winogrande(0-Shot)
- task:
type: text-generation
dataset:
name: arc_challenge
type: arc_challenge
metrics:
- type: arc_challenge (0-Shot)
value: 0.3712
name: arc_challenge(0-Shot)
source:
url: https://huggingface.co./mwitiderrick/open_llama_3b_instruct_v_0.2
name: open_llama_3b_instruct_v_0.2 model card
DavidAU/open_llama_3b_code_instruct_0.1-Q6_K-GGUF
This model was converted to GGUF format from mwitiderrick/open_llama_3b_code_instruct_0.1
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.
brew install ggerganov/ggerganov/llama.cpp
Invoke the llama.cpp server or the CLI.
CLI:
llama-cli --hf-repo DavidAU/open_llama_3b_code_instruct_0.1-Q6_K-GGUF --model open_llama_3b_code_instruct_0.1.Q6_K.gguf -p "The meaning to life and the universe is"
Server:
llama-server --hf-repo DavidAU/open_llama_3b_code_instruct_0.1-Q6_K-GGUF --model open_llama_3b_code_instruct_0.1.Q6_K.gguf -c 2048
Note: You can also use this checkpoint directly through the usage steps listed in the Llama.cpp repo as well.
git clone https://github.com/ggerganov/llama.cpp && cd llama.cpp && make && ./main -m open_llama_3b_code_instruct_0.1.Q6_K.gguf -n 128