metadata
pipeline_tag: text-generation
base_model: ibm-granite/granite-8b-code-instruct-4k
inference: false
license: apache-2.0
datasets:
- bigcode/commitpackft
- TIGER-Lab/MathInstruct
- meta-math/MetaMathQA
- glaiveai/glaive-code-assistant-v3
- glaive-function-calling-v2
- bugdaryan/sql-create-context-instruction
- garage-bAInd/Open-Platypus
- nvidia/HelpSteer
metrics:
- code_eval
library_name: transformers
tags:
- code
- granite
- openvino
- openvino-export
model-index:
- name: granite-8b-code-instruct-4k
results:
- task:
type: text-generation
dataset:
name: HumanEvalSynthesis(Python)
type: bigcode/humanevalpack
metrics:
- type: pass@1
value: 57.9
name: pass@1
- type: pass@1
value: 52.4
name: pass@1
- type: pass@1
value: 58.5
name: pass@1
- type: pass@1
value: 43.3
name: pass@1
- type: pass@1
value: 48.2
name: pass@1
- type: pass@1
value: 37.2
name: pass@1
- type: pass@1
value: 53
name: pass@1
- type: pass@1
value: 42.7
name: pass@1
- type: pass@1
value: 52.4
name: pass@1
- type: pass@1
value: 36.6
name: pass@1
- type: pass@1
value: 43.9
name: pass@1
- type: pass@1
value: 16.5
name: pass@1
- type: pass@1
value: 39.6
name: pass@1
- type: pass@1
value: 40.9
name: pass@1
- type: pass@1
value: 48.2
name: pass@1
- type: pass@1
value: 41.5
name: pass@1
- type: pass@1
value: 39
name: pass@1
- type: pass@1
value: 32.9
name: pass@1
This model was converted to OpenVINO from ibm-granite/granite-8b-code-instruct-4k using optimum-intel
via the export space.
First make sure you have optimum-intel installed:
pip install optimum[openvino]
To load your model you can do as follows:
from optimum.intel import OVModelForCausalLM
model_id = "NitroLLM/granite-8b-code-instruct-4k-openvino"
model = OVModelForCausalLM.from_pretrained(model_id)