From: zed-industries <huggingface.co/zed-industries>Newsgroups: alt.freeweights.textSubject:

zeta

Date: 2026-11-15Commit: 80f73ceSigned: 2DC28CC7B26A283B ✓

Model with 7.6B parameters. Safetensors weights, 15.2 GB in all. Published by zed-industries under Apache-2.0.

7.6B params15.2GBzetasafetensorspermissive
FactsParams7.6BSize15.2 GBFormatssafetensorsTasknot taggedLicenseApache-2.0From sourcepermissive
$ fw get zed-industries/zeta
# manifest sha256 41516d7f5bdb… · 15.2 GB · 15 files
$ fw verify ./zeta zed-industries/zeta
From sourceHosted (signed)zed-industries/zetaLast check: 2026-11-15 02:27 UTC

Get help: custom fine-tune or private deploy. We review your setup before we quote.

Works with

Runs with

Ranked by fit to this model (safetensors), then by GitHub stars.

Overview

Size
15.2 GB
Weights
15.2 GB (safetensors)
Parameters
7.6B
Formats
safetensors
Task
not tagged
License
Apache-2.0 (permissive)
Files
15, each with a sha256
Publisher
zed-industries
Added
2026-11-15
Section
alt.freeweights.text
Lineage

Original release from the publisher.

Where these bytes come from
Publisher at the pinned commit→You

Sources are tried in order. A file counts only when its size and sha256 match the manifest. Sources are checked when you ask for them, not on a timer.

Sources
BadgeHostLast checkResult
From sourcehuggingface.co2026-11-15 02:27 UTCpassed

Model card

From the publisher at commit 80f73ce. Shown as plain text with links; images open at the publisher.

Image: image

Edit Prediction: Fine-Tuned from Qwen2.5-Coder-7B#

This repository contains a fine-tuned version of Qwen2.5-Coder-7B to support edit prediction in Zed.

Training Details#

The model has been fine-tuned using the zeta dataset. If you want to fine-tune the model yourself, you can refer to the following scripts:

Dataset#

The dataset used for training is available at: zed-industries/zeta

Running Zeta#

vLLM - Simple#

vllm serve zed-industries/zeta --served-model-name zeta

vLLM - Advanced#
  • Quantization vLLM supports FP8 (8-bit floating point) weight and activation quantization using hardware acceleration on GPUs such as Nvidia H100 and AMD MI300x.
  • NGram Speculative Decoding configures vLLM to use

speculative decoding where proposals are generated by matching n-grams in the prompt. This is a great fit for edit predictions since many of the tokens are already present in the prompt and the model is only needed to generate changes to the code file.

vllm serve zed-industries/zeta --served-model-name zeta --enable-prefix-caching --enable-chunked-prefill --quantization="fp8" --speculative-model [ngram] --ngram-prompt-lookup-max 4 --ngram-prompt-lookup-min 2 --num-speculative-tokens 8

Learn More#

For more insights about the model and its integration in Zed, check out the official blog post: Zed Blog - Edit Prediction

Files

15 files · 15.2 GBWeights 15.2 GB (safetensors). Sizes and sha256 from the signed manifest.
Hide all 15 files with their sha256
FileSizesha256
.gitattributes1.57 KB34448b82c17d60fec9b65b1f093c115ddbaadc04beb1b0140b6bfed2e012a930
README.md2.15 KBc66208e8edcdfc091706f2ab0e0b4319a2a270a2e3eca000026a8d3c5f836cc0
added_tokens.json632 Ba32bc0d990603eb93fd389dc164fe6fbfc442db2ab3a65e4a99a249433ab11f6
config.json800 B4f97a6b100af6a5a084e4fb3796d8d8175a8879ac979c1ec7ae1dbe6a2047168
generation_config.json166 Bd4335667a857b09494b01a2a0991f3b1bb088cfc93d37983037904d95e19b784
merges.txt1.67 MB8831e4f1a044471340f7c0a83d7bd71306a5b867e95fd870f74d0c5308a904d5
model-00001-of-00004.safetensors4.88 GB0b6fafe5576afc1057528d577020b95e004e5b13dec5e18d9e0cf17ed18d96a8
model-00002-of-00004.safetensors4.93 GB7993c882adcdbb8931ce1a040f2b5ca9f94968c8541544fd21eb39ebd2703d3a
model-00003-of-00004.safetensors4.33 GB1786a21c254e98ea92cffd6fe52641f30e03f6b7f23db73541be8a354bb1b355
model-00004-of-00004.safetensors1.09 GB0167e1c1b01ce71c87dd479157695cc1667342b9d2d75d2a64a648dfbaf04b8f
model.safetensors.index.json27.8 KB998a078123ffc97763690de7f2a677eb89168af5eaf8a5e12e6bc24d18e25bdb
special_tokens_map.json616 Ba6a53a38d0f1a08d04fae3ae1a48ce49b3d862b994ed5e4736ed7701cf9236bf
tokenizer.json11.4 MBfab42efe8d17406525a9154b728cf9e957629a8ed7ce997770efdd71128c6a1a
tokenizer_config.json4.89 KB2de612e84ebf57a79c6d6af904f98b616b8064c62664ed57d425446f526dd06c
vocab.json2.78 MBca10d7e9fb3ed18575dd1e277a2579c16d108e32f27439684afa0e10b1440910
VersionsEach time the pinned upstream commit or file list changed in this repo. Newest first.
Upstream commitDateContents
80f73ce5ee pinned now2026-11-15 02:27 UTC15 files · 15.2 GB

Use it

$ fw get zed-industries/zeta
# manifest sha256 41516d7f5bdb… · 15.2 GB · 15 files
$ fw verify ./zeta zed-industries/zeta
fw.pyChecks the signature and every sha256, tries each source in order, resumes.
$ python3 fw.py get https://freeweights.allternit.com/manifests/zed-industries/zeta.json --dir ./zeta $ python3 fw.py verify ./zeta ./zed-industries__zeta.json
hfThe Hugging Face CLI with one setting. Same repo id.
$ HF_ENDPOINT=https://freeweights.allternit.com hf download zed-industries/zeta --revision 80f73ce5ee059377ce0662ec5c45b592c3025ae5 --local-dir ./zeta

License

Name
Apache License 2.0
Id
Apache-2.0
Class
Permissive
Redistribution
yes
Listing
Hosted (signed)
Decided
License as declared by the publisher. No person read it. 2026-11-15
Text in
README.md
Text sha256
c66208e8edcdfc091706f2ab0e0b4319a2a270a2e3eca000026a8d3c5f836cc0
Terms gate
No extra terms beyond the license.

Read the license text

Licenses are checked against the license table. A custom license passes only after a person reads it.

Provenance

From: zed-industries <huggingface.co/zed-industries>Newsgroups: alt.freeweights.textSubject: zetaDate: 2026-11-15Commit: 80f73ceSigned: 2DC28CC7B26A283B ✓
Upstream
zed-industries/zeta
Pinned commit
80f73ce5ee059377ce0662ec5c45b592c3025ae5
Manifest
zeta.json · .minisig
Manifest sha256
41516d7f5bdb864560d08574488afd849e055c5fd973f03cb8421c1ffbd48c02
Signature
minisign, Ed25519, key 2DC28CC7B26A283B
Created
2026-11-15 02:27 UTC
Generator
freeweights-manifest/0.1.0
Takedowns
None.

How to verify

$ curl -O https://freeweights.allternit.com/manifests/zed-industries/zeta.json $ curl -O https://freeweights.allternit.com/manifests/zed-industries/zeta.json.minisig $ minisign -Vm zeta.json -P RWQ7KGqyx4zCLXtUFOqvfv8L3g+8fpKJ1FsuxPyOYMF+4KufbUxKq1Oq $ shasum -a 256 <file> # compare with the Files tab

A manifest whose signature fails must be rejected. A file whose size or sha256 does not match must be discarded. Verify a download

Model tree

1 model in the catalog name this one as their parent.

Quantizations
1
Quantizations 1
Get it
Download
$ HF_ENDPOINT=https://freeweights.allternit.com hf download zed-industries/zeta
Open in Freeweights Studio

Pull, verify and run it in the Allternit app on Desktop, web or phone.

Signed manifest
minisign, key 2DC28CC7B26A283B. zeta.json. Provenance. Takedown history: none.

Variants

1 quantized or adapter build of zeta. Each has its own license check and page.

From: laion <huggingface.co/laion>Subject: a2-rl-e2egit_large-50-32B
From: laion <huggingface.co/laion>Subject: a3-rl-DCAgent_exp_rpt_e2egit-large-15-8B
From: laion <huggingface.co/laion>Subject: a3-rl-DCAgent_exp_rpt_e2egit-v2-10-8B
From: laion <huggingface.co/laion>Subject: a3-rl-DCAgent_exp_rpt_pymethods2test-large-80-8B
From: laion <huggingface.co/laion>Subject: a3-rl-DCAgent_exp_rpt_unitsyn-python-large-10-8B
From: laion <huggingface.co/laion>Subject: a3-rl-DCAgent_mix_h2_language_proportional-65-8B