alt.freeweights.qwen / Qwen2.5-Coder-1.5B-Instruct
From: onnx-community <huggingface.co/onnx-community>Newsgroups: alt.freeweights.qwenSubject:

Qwen2.5-Coder-1.5B-Instruct

Date: 2026-11-15Commit: 774cc90Signed: 2DC28CC7B26A283B ✓

Text generation model. Onnx weights, 21.2 GB in all. Published by onnx-community under Apache-2.0.

qwen21.2GBQwen2.5-Coder-1.5B-Instructonnxpermissive
FactsParamsnot statedSize21.2 GBFormatsonnxTasktext generationLicenseApache-2.0From sourcepermissive
$ fw get onnx-community/Qwen2.5-Coder-1.5B-Instruct
# manifest sha256 5e3ba69721e9… · 21.2 GB · 21 files
$ fw verify ./Qwen2.5-Coder-1.5B-Instruct onnx-community/Qwen2.5-Coder-1.5B-Instruct
From sourceHosted (signed)onnx-community/Qwen2.5-Coder-1.5B-InstructLast check: 2026-11-15 05:07 UTC

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

Quantized of Qwen2.5-Coder-1.5B-Instruct.

Works with

Runs with

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

Convert with

Overview

Size
21.2 GB
Weights
1.34 GB (smallest of 8 ONNX variants)
Parameters
not stated
Formats
onnx
Task
text generation
License
Apache-2.0 (permissive)
Files
21, each with a sha256
Publisher
onnx-community
Added
2026-11-15
Section
alt.freeweights.qwen
Lineage

Original release from the publisher.

Base model: Qwen/Qwen2.5-Coder-1.5B-Instruct

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 05:07 UTCpassed

Model card

From the publisher at commit 774cc90. Shown as plain text with links; images open at the publisher.

https://huggingface.co/Qwen/Qwen2.5-Coder-1.5B-Instruct with ONNX weights to be compatible with Transformers.js.

Usage (Transformers.js)#

If you haven't already, you can install the Transformers.js JavaScript library from NPM using:

npm i @huggingface/transformers

Example: Text generation with onnx-community/Qwen2.5-Coder-1.5B-Instruct.

import { pipeline } from "@huggingface/transformers";

// Create a text generation pipeline
const generator = await pipeline(
  "text-generation",
  "onnx-community/Qwen2.5-Coder-1.5B-Instruct",
  { dtype: "q4" },
);

// Define the list of messages
const messages = [
  { role: "system", content: "You are a helpful assistant." },
  { role: "user", content:  "Write a quick sort algorithm." },
];

// Generate a response
const output = await generator(messages, { max_new_tokens: 512, do_sample: false });
console.log(output[0].generated_text.at(-1).content);

Example output

Sure! Below is the implementation of the QuickSort algorithm in Python:

def quicksort(arr): if len(arr) <= 1: return arr

pivot = arr[len(arr) // 2]

left = [x for x in arr if x < pivot] middle = [x for x in arr if x == pivot] right = [x for x in arr if x > pivot]

return quicksort(left) + middle + quicksort(right)

Example usage:#

arr = [3, 6, 8, 10, 1, 2, 1] print("Original array:", arr) sorted_arr = quicksort(arr) print("Sorted array:", sorted_arr)


### Explanation:
- **Base Case**: If the length of the list `arr` is less than or equal to one (`len(arr) <= 1`), it means the list is already sorted and can be returned as it is.
- **Pivot Selection**: The chosen `pivot` element can be any element from the list (e.g., `len(arr)//2`). For simplicity here we choose this way.
- **Partitioning**:
   - Elements less than or equal to `pivot` are placed into a new list called `left`.
   - Elements equal to `pivot` are placed into another new list called `middle`.
   - Elements greater than or equal to `pivot` are placed into yet another new list called `right`.
- **Recursive Sorting**: The function recursively applies itself on these three lists (`left`, middle`, and right`) and concatenates them back together.

This implementation ensures that all elements less than or equal to any given element will appear before that element in their respective partitions.

Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using 🤗 Optimum and structuring your repo like this one (with ONNX weights located in a subfolder named onnx).

Files

21 files · 21.2 GBWeights 1.34 GB (smallest of 8 ONNX variants). Sizes and sha256 from the signed manifest.
Show all 21 files with their sha256
FileSizesha256
.gitattributes1.69 KB9002b3569bc2ce0e14144f5d52ea5e964666580156ee3ee3549ead8a9d0624c2
README.md3.01 KBdec4a9931a394ff9cd7bfe0110abab1fea76aea14e8ad3fcce5e5c8f89470586
added_tokens.json605 B58b54bbe36fc752f79a24a271ef66a0a0830054b4dfad94bde757d851968060b
config.json948 Bdebf0b90deaf6cbcb066fc26e048d4f14414828114a206b09f263730b1ad7f3c
generation_config.json242 B0dc30d5b7f022dcbfaaef3e55340642208a3b0436214346caf1c522c009f699d
merges.txt1.67 MB8831e4f1a044471340f7c0a83d7bd71306a5b867e95fd870f74d0c5308a904d5
onnx/model.onnx532 KBf8a2891765a8cfb5fbf76235fcb99f84d57a47430f9efeb24ef400e17c91d019
onnx/model.onnx_data7.13 GB0a11022897439e8f65c9882338322897453a05abe3435b5ed38094e128f0c080
onnx/model_bnb4.onnx1.82 GBa22d663bf3915f9c5a111d5be6299e18d22d5f503ce8aaa31231eff11c995779
onnx/model_fp16.onnx534 KB266034903747b160bbc23f7a8689c69d622a34941b94d54543d5374b1d694009
onnx/model_fp16.onnx_data3.56 GB69b1fd26da7afc014e57b7a64cef8265bd545809f358798b48e0af784400e6d1
onnx/model_int8.onnx1.80 GB92f3b69db6c85669db5ed18d501a6e47f8aaf849b847a3c27a2014905db1cc17
onnx/model_q4.onnx1.92 GB3be13b6b30c1c152bd36e5a886a36800d404f56494c74e2fdf1d634d175372e1
onnx/model_q4f16.onnx1.34 GB0e33cbfde4be371039daad0032fb3782170442e6901a25d4deabe96117b89882
onnx/model_quantized.onnx1.80 GB92f3b69db6c85669db5ed18d501a6e47f8aaf849b847a3c27a2014905db1cc17
onnx/model_uint8.onnx1.80 GB967d74ee65ca2ee796697b90b2875f24255ead1ea9d2861cbafc592987861ba6
quantize_config.json285 B8da6e4e50ef7c210ba66a98a4256e6d60e38cef8a9a9c74d327251aaf4e78767
special_tokens_map.json613 B76862e765266b85aa9459767e33cbaf13970f327a0e88d1c65846c2ddd3a1ecd
tokenizer.json11.4 MB9c5ae00e602b8860cbd784ba82a8aa14e8feecec692e7076590d014d7b7fdafa
tokenizer_config.json7.85 KB6a14243f0ae04884e597b3f032c05e15de9f417318fdcac24ab4e2680e691430
vocab.json2.78 MBca10d7e9fb3ed18575dd1e277a2579c16d108e32f27439684afa0e10b1440910
VersionsEach time the pinned upstream commit or file list changed in this repo. Newest first.
Upstream commitDateContents
774cc908b6 pinned now2026-11-15 05:07 UTC21 files · 21.2 GB

Use it

$ fw get onnx-community/Qwen2.5-Coder-1.5B-Instruct
# manifest sha256 5e3ba69721e9… · 21.2 GB · 21 files
$ fw verify ./Qwen2.5-Coder-1.5B-Instruct onnx-community/Qwen2.5-Coder-1.5B-Instruct
fw.pyChecks the signature and every sha256, tries each source in order, resumes.
$ python3 fw.py get https://freeweights.allternit.com/manifests/onnx-community/Qwen2.5-Coder-1.5B-Instruct.json --dir ./Qwen2.5-Coder-1.5B-Instruct $ python3 fw.py verify ./Qwen2.5-Coder-1.5B-Instruct ./onnx-community__Qwen2.5-Coder-1.5B-Instruct.json
hfThe Hugging Face CLI with one setting. Same repo id.
$ HF_ENDPOINT=https://freeweights.allternit.com hf download onnx-community/Qwen2.5-Coder-1.5B-Instruct --revision 774cc908b6c2be23bc4e8d4e401e4f8b8fba7daf --local-dir ./Qwen2.5-Coder-1.5B-Instruct

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
dec4a9931a394ff9cd7bfe0110abab1fea76aea14e8ad3fcce5e5c8f89470586
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: onnx-community <huggingface.co/onnx-community>Newsgroups: alt.freeweights.qwenSubject: Qwen2.5-Coder-1.5B-InstructDate: 2026-11-15Commit: 774cc90Signed: 2DC28CC7B26A283B ✓
Upstream
onnx-community/Qwen2.5-Coder-1.5B-Instruct
Pinned commit
774cc908b6c2be23bc4e8d4e401e4f8b8fba7daf
Manifest
Qwen2.5-Coder-1.5B-Instruct.json · .minisig
Manifest sha256
5e3ba69721e926b4cbc311972688fafc7cb5babac07cfd76b6e75316adad300a
Signature
minisign, Ed25519, key 2DC28CC7B26A283B
Created
2026-11-15 05:07 UTC
Generator
freeweights-manifest/0.1.0
Takedowns
None.

How to verify

$ curl -O https://freeweights.allternit.com/manifests/onnx-community/Qwen2.5-Coder-1.5B-Instruct.json $ curl -O https://freeweights.allternit.com/manifests/onnx-community/Qwen2.5-Coder-1.5B-Instruct.json.minisig $ minisign -Vm Qwen2.5-Coder-1.5B-Instruct.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

Parent

Qwen/Qwen2.5-Coder-1.5B-Instruct · this model is a quantization of it

No model in the catalog names this one as its parent.

Get it
Download
$ HF_ENDPOINT=https://freeweights.allternit.com hf download onnx-community/Qwen2.5-Coder-1.5B-Instruct
Open in Freeweights Studio

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

Signed manifest
minisign, key 2DC28CC7B26A283B. Qwen2.5-Coder-1.5B-Instruct.json. Provenance. Takedown history: none.
From: BAAI <huggingface.co/BAAI>Subject: Aquila-VL-2B-llava-qwen
From: Perciqa <huggingface.co/Perciqa>Subject: Aurora-Code-1
From: BAAI <huggingface.co/BAAI>Subject: bge-reasoner-embed-qwen3-8b-0923
From: amazon <huggingface.co/amazon>Subject: BMOJOF-primed-HQwen3-8B-Instruct
From: nbeerbower <huggingface.co/nbeerbower>Subject: Bubba-Qwen3.6-27B-LoRA
From: bartowski <huggingface.co/bartowski>Subject: bytkim_Qwen3.8-27B-pi-GGUF