Edit model card

speechless-coder-ds-6.7b

4, 5 and 8-bit GGUF models for CPU+GPU inference

Use the following dataset to fine-tune deepseek-ai/deepseek-coder-6.7b in order to improve the model's reasoning and planning abilities.

context window length: 8192 max_tokens > 128 && < 8192

Total 185,193 samples 426 MB

  • ise-uiuc/Magicoder-OSS-Instruct-75K 75,186 samples
  • ise-uiuc/Magicoder-Evol-Instruct-110K 110,007 samples

50 samples/T=0.2/MaxTokens=512/Top_P=0.95

Code: https://github.com/uukuguy/speechless

How to Prompt the Model

This model accepts the Alpaca instruction format.

For example:

You are an intelligent programming assistant.

### Instruction:
Implement a linked list in C++

### Response:

HumanEval

Metric Value
humaneval-python

Big Code Models Leaderboard

CodeLlama-34B-Python: 53.29

CodeLlama-34B-Instruct: 50.79

CodeLlama-13B-Instruct: 50.6

CodeLlama-34B: 45.11

CodeLlama-13B-Python: 42.89

CodeLlama-13B: 35.07

BigCode Eval

0.314188

  • metrics_humanevalfixtests-cpp: "pass@1": 0.27439024390243905
  • metrics_humanevalfixtests-go: "pass@1": 0.23170731707317074
  • metrics_humanevalfixtests-java: "pass@1": 0.25609756097560976
  • metrics_humanevalfixtests-js: "pass@1": 0.21951219512195122
  • metrics_humanevalfixtests-python: "pass@1": 0.23780487804878048
  • metrics_humanevalfixtests-rust: "pass@1": 0.13414634146341464

0.390111

  • metrics_humanevalsynthesize-cpp: "pass@1": 0.3780487804878049
  • metrics_humanevalsynthesize-go: "pass@1": 0.25609756097560976
  • metrics_humanevalsynthesize-java: "pass@1": 0.45121951219512196
  • metrics_humanevalsynthesize-js: "pass@1": 0.4268292682926829
  • metrics_humanevalsynthesize-python: "pass@1": 0.5365853658536586
  • metrics_humanevalsynthesize-rust: "pass@1": 0.25
  • metrics_mbpp: "pass@1": 0.432

LMEval

Open LLM Leaderboard

Metric Value
ARC
HellaSwag
MMLU
TruthfulQA
Average
Downloads last month
798
GGUF
Model size
6.74B params
Architecture
llama

4-bit

5-bit

8-bit

Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Datasets used to train uukuguy/speechless-coder-ds-6.7b

Collection including uukuguy/speechless-coder-ds-6.7b

Evaluation results