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Granite 3B Code Instruct GGUF
Model creator: ibm-granite
Original model: granite-3b-code-instruct
Model Summary:
Granite-3B-Code-Instruct is a 3B parameter model fine tuned from Granite-3B-Code-Base on a combination of permissively licensed instruction data to enhance instruction following capabilities including logical reasoning and problem-solving skills.
- Developers: IBM Research
- GitHub Repository: ibm-granite/granite-code-models
- Paper: Granite Code Models: A Family of Open Foundation Models for Code Intelligence
- Release Date: May 6th, 2024
- License: Apache 2.0.
Prompt Template:
If you're using Sanctum app, simply use IBM Granite Code
model preset.
Prompt template:
System:
{system_prompt}
Question:
{prompt}
Answer:
Hardware Requirements Estimate
Name | Quant method | Size | Memory (RAM, vRAM) required (for full context of 32k tokens) |
---|---|---|---|
granite-3b-code-instruct.Q2_K.gguf | Q2_K | 1.34 GB | 4.68 GB |
granite-3b-code-instruct.Q3_K_S.gguf | Q3_K_S | 1.55 GB | ? |
granite-3b-code-instruct.Q3_K_M.gguf | Q3_K_M | 1.73 GB | ? |
granite-3b-code-instruct.Q3_K_L.gguf | Q3_K_L | 1.88 GB | ? |
granite-3b-code-instruct.Q4_0.gguf | Q4_0 | 2.00 GB | ? |
granite-3b-code-instruct.Q4_K_S.gguf | Q4_K_S | 2.01 GB | ? |
granite-3b-code-instruct.Q4_K_M.gguf | Q4_K_M | 2.13 GB | ? |
granite-3b-code-instruct.Q4_K.gguf | Q4_K | 2.13 GB | ? |
granite-3b-code-instruct.Q4_1.gguf | Q4_1 | 2.21 GB | ? |
granite-3b-code-instruct.Q5_0.gguf | Q5_0 | 2.42 GB | ? |
granite-3b-code-instruct.Q5_K_S.gguf | Q5_K_S | 2.42 GB | ? |
granite-3b-code-instruct.Q5_K_M.gguf | Q5_K_M | 2.49 GB | ? |
granite-3b-code-instruct.Q5_K.gguf | Q5_K | 2.49 GB | ? |
granite-3b-code-instruct.Q5_1.gguf | Q5_1 | 2.63 GB | ? |
granite-3b-code-instruct.Q6_K.gguf | Q6_K | 2.86 GB | ? |
granite-3b-code-instruct.Q8_0.gguf | Q8_0 | 3.71 GB | ? |
granite-3b-code-instruct.f16.gguf | f16 | 6.97 GB | 4.68 GB |
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Model tree for SanctumAI/granite-3b-code-instruct-GGUF
Base model
ibm-granite/granite-3b-code-base-2kDatasets used to train SanctumAI/granite-3b-code-instruct-GGUF
Evaluation results
- pass@1 on HumanEvalSynthesis(Python)self-reported51.200
- pass@1 on HumanEvalSynthesis(JavaScript)self-reported43.900
- pass@1 on HumanEvalSynthesis(Java)self-reported41.500
- pass@1 on HumanEvalSynthesis(Go)self-reported31.700
- pass@1 on HumanEvalSynthesis(C++)self-reported40.200
- pass@1 on HumanEvalSynthesis(Rust)self-reported29.300
- pass@1 on HumanEvalExplain(Python)self-reported39.600
- pass@1 on HumanEvalExplain(JavaScript)self-reported26.800
- pass@1 on HumanEvalExplain(Java)self-reported39.000
- pass@1 on HumanEvalExplain(Go)self-reported14.000