What are the hardware requirements for Datascience Coder 6.7B?

Datascience Coder 6.7B requires approximately 13.5 GB of VRAM and supports a context window of 16K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Datascience Coder 6.7B and how large is it?

Datascience Coder 6.7B is developed by ed001, a model with 6.7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Datascience Coder 6.7B perform on standard benchmarks?

Datascience Coder 6.7B has the following published scores: MMLU 37.96. Compare against reference models on this page or on the LLM Explorer leaderboards.

Datascience Coder 6.7B by ed001 — VRAM 13.5GB, 16K context

Name: Datascience Coder 6.7B
Author: ed001

Datascience Coder 6.7B is an open-source language model by ed001. Features: 6.7b LLM, VRAM: 13.5GB, Context: 16K, License: cc-by-nc-sa-4.0, Instruction-Based, Code Generating, LLM Explorer Score: 0.14, Arc: 34.6, HellaSwag: 53.8, MMLU: 38, GSM8K: 24.9.

Code Codegen Conversational Data science Dataset:ed001/ds-coder-instruc... En Endpoints compatible Instruct Llama Model-index Pytorch Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/ed001/datascience-coder-6.7b

Datascience Coder 6.7B Parameters and Internals

Model Type

text-generation

Additional Notes

Trained on the Python subset of the ds-coder-instruct dataset.

Training Details

Data Sources:

ed001/ds-coder-instruct-v1

Methodology:

fine-tuned

Context Length:

4096

Input Output

Accepted Modalities:

text

Output Format:

text

LLM Name	Datascience Coder 6.7B
Repository 🤗	https://huggingface.co/ed001/datascience-coder-6.7b
Model Size	6.7b
Required VRAM	13.5 GB
Updated	2026-07-24
Maintainer	ed001
Model Type	llama
Instruction-Based	Yes
Model Files	10.0 GB: 1-of-2 3.5 GB: 2-of-2 10.0 GB: 1-of-2 3.5 GB: 2-of-2
Supported Languages	en
Generates Code	Yes
Model Architecture	LlamaForCausalLM
License	cc-by-nc-sa-4.0
Context Length	16384
Model Max Length	16384
Transformers Version	4.31.0
Tokenizer Class	LlamaTokenizer
Beginning of Sentence Token	<｜begin▁of▁sentence｜>
End of Sentence Token	<\|EOT\|>
Vocabulary Size	32256
Torch Data Type	float16

Rank the Datascience Coder 6.7B capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Best Alternatives to Datascience Coder 6.7B

Best Alternatives	Context / RAM	Downloads	Likes
Speechless Coder Ds 6.7B	16K / 13.5 GB	459	7
...s Coder6.7b Reflct Adamw Iter1	16K / 13.5 GB	475	0
...Coder6.7b Reflct Rmsprop Iter1	16K / 13.5 GB	95	0
...Coder6.7b Reflct Rmsprop Iter1	16K / 13.5 GB	110	0
...r6.7b Pos Reflct Rmsprop Iter1	16K / 13.5 GB	87	0
...ir4 Ds Coder6.7b Rmsprop Iter1	16K / 13.5 GB	43	0
Code 290K 6.7B Instruct	16K / 13.5 GB	87	6
...r6.7b Pos Reflct Rmsprop Iter1	16K / 13.5 GB	90	0
...Coder6.7b Reflct Rmsprop Iter1	16K / 13.5 GB	62	0
Ds Coder6.7b Rmsprop Iter1	16K / 13.5 GB	67	0

Note: green Score (e.g. "73.2") means that the model is better than ed001/datascience-coder-6.7b.