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alt.freeweights.smollm / SmolLM2-360M-Instruct
From: unsloth <huggingface.co/unsloth>Newsgroups: alt.freeweights.smollmSubject:

SmolLM2-360M-Instruct

Date: 2026-11-15Commit: 7c6bf9aSigned: 2DC28CC7B26A283B ✓

Text generation model with 362M parameters. Safetensors weights, 728 MB in all. Published by unsloth under Apache-2.0.

362M params728MBSmolLM2-360M-Instructsafetensorspermissive
FactsParams362MSize728 MBFormatssafetensorsTasktext generationLicenseApache-2.0From sourcepermissive
$ fw get unsloth/SmolLM2-360M-Instruct
# manifest sha256 40c0621b60c3… · 728 MB · 11 files
$ fw verify ./SmolLM2-360M-Instruct unsloth/SmolLM2-360M-Instruct
From sourceHosted (signed)unsloth/SmolLM2-360M-InstructLast check: 2026-11-15 03:28 UTC
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OverviewModel cardFilesUse itLicenseProvenanceModel tree

Overview

Size
728 MB
Weights
724 MB (safetensors)
Parameters
362M
Formats
safetensors
Task
text generation
License
Apache-2.0 (permissive)
Files
11, each with a sha256
Publisher
unsloth
Added
2026-11-15
Section
alt.freeweights.smollm
Lineage

Original release from the publisher.

Base model: HuggingFaceTB/SmolLM2-360M-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 03:28 UTCpassed

Model card

From the publisher at commit 7c6bf9a. Shown as plain text with links; images open at the publisher.

Finetune SmolLM2, Llama 3.2, Gemma 2, Mistral 2-5x faster with 70% less memory via Unsloth!#

We have a free Google Colab Tesla T4 notebook for Llama 3.2 (3B) here: https://colab.research.google.com/drive/1Ys44kVvmeZtnICzWz0xgpRnrIOjZAuxp?usp=sharing

https://discord.gg/unsloth https://github.com/unslothai/unsloth

unsloth/SmolLM2-360M Instruct#

For more details on the model, please go to Hugging Face's original model card

✨ Finetune for Free#

All notebooks are beginner friendly! Add your dataset, click "Run All", and you'll get a 2x faster finetuned model which can be exported to GGUF, vLLM or uploaded to Hugging Face.

Unsloth supportsFree NotebooksPerformanceMemory use
Llama-3.2 (3B)▶️ Start on Colab2.4x faster58% less
Llama-3.2 (11B vision)▶️ Start on Colab2.4x faster58% less
Llama-3.1 (8B)▶️ Start on Colab2.4x faster58% less
Phi-3.5 (mini)▶️ Start on Colab2x faster50% less
Gemma 2 (9B)▶️ Start on Colab2.4x faster58% less
Mistral (7B)▶️ Start on Colab2.2x faster62% less
DPO - Zephyr▶️ Start on Colab1.9x faster19% less

Special Thanks#

A huge thank you to the Hugging Face team for creating and releasing these models.

Model Summary#

SmolLM2 is a family of compact language models available in three size: 135M, 360M, and 1.7B parameters. They are capable of solving a wide range of tasks while being lightweight enough to run on-device.

The 1.7B variant demonstrates significant advances over its predecessor SmolLM1-1.7B, particularly in instruction following, knowledge, reasoning, and mathematics. It was trained on 11 trillion tokens using a diverse dataset combination: FineWeb-Edu, DCLM, The Stack, along with new mathematics and coding datasets that we curated and will release soon. We developed the instruct version through supervised fine-tuning (SFT) using a combination of public datasets and our own curated datasets. We then applied Direct Preference Optimization (DPO) using UltraFeedback.

The instruct model additionally supports tasks such as text rewriting, summarization and function calling thanks to datasets developed by Argilla such as Synth-APIGen-v0.1.

SmolLM2#

Image: image/png

Files

11 files · 728 MBWeights 724 MB (safetensors). Sizes and sha256 from the signed manifest.
Hide all 11 files with their sha256
FileSizesha256
.gitattributes1.52 KB11ad7efa24975ee4b0c3c3a38ed18737f0658a5f75a0a96787b576a78a023361
README.md4.56 KBbe2ff596e067105d65140db726c7497eae60907d3fd07cf6d4a663c8c1bc76a6
added_tokens.json29 B5a7038c26cb1d019b0258d86889308341cf8c0166978b05f5996be953bb69c9e
config.json926 B1c15ee4277ad8cd8a6aa8e07f2b54ee72bc231fa45a3e69a93e71b48aa87f2cb
generation_config.json158 Bafb4d81568aa62eee418471ca6973ce906e0d21c1737aa3a6a4c697e00872e8d
merges.txt466 KB0b54e8aa4e53d5383e2e4bc635a56b43f9647f7b13832d5d9ecd8f82dac4f510
model.safetensors724 MB2202f971b79ea8f74bccf46e64b8cdab780f8f3280d06c96a67e52e03545d274
special_tokens_map.json423 B8d39b597d486de3dd50200e067b418cb42ed5fd9b9fd0b4cfd8871eae9c65e1c
tokenizer.json3.52 MB66bfc9a0d05ad54eef8e1f906d77fd37663e8a51eb1c56b44d2e4227448f91fb
tokenizer_config.json3.96 KBbf4e0fd676862c396f9c6317c11fe3b395dc1f8fd5e6b48265d4a8d39e500588
vocab.json801 KB82b84012e3add4d01d12ba14442026e49b8cbbaead1f79ecf3d919784f82dc79
VersionsEach time the pinned upstream commit or file list changed in this repo. Newest first.
Upstream commitDateContents
7c6bf9a2fa pinned now2026-11-15 03:28 UTC11 files · 728 MB

Use it

$ fw get unsloth/SmolLM2-360M-Instruct
# manifest sha256 40c0621b60c3… · 728 MB · 11 files
$ fw verify ./SmolLM2-360M-Instruct unsloth/SmolLM2-360M-Instruct
fw.pyChecks the signature and every sha256, tries each source in order, resumes.
$ python3 fw.py get https://freeweights.allternit.com/manifests/unsloth/SmolLM2-360M-Instruct.json --dir ./SmolLM2-360M-Instruct $ python3 fw.py verify ./SmolLM2-360M-Instruct ./unsloth__SmolLM2-360M-Instruct.json
hfThe Hugging Face CLI with one setting. Same repo id.
$ HF_ENDPOINT=https://freeweights.allternit.com hf download unsloth/SmolLM2-360M-Instruct --revision 7c6bf9a2faef35209646cd7f1569fae2b2394a00 --local-dir ./SmolLM2-360M-Instruct
transformersLoad the weights in Python.
import os os.environ["HF_ENDPOINT"] = "https://freeweights.allternit.com" from transformers import AutoModelForCausalLM, AutoTokenizer tok = AutoTokenizer.from_pretrained("unsloth/SmolLM2-360M-Instruct", revision="7c6bf9a2faef35209646cd7f1569fae2b2394a00") model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM2-360M-Instruct", revision="7c6bf9a2faef35209646cd7f1569fae2b2394a00", device_map="auto")
vLLMServe an OpenAI-compatible API.
$ HF_ENDPOINT=https://freeweights.allternit.com vllm serve unsloth/SmolLM2-360M-Instruct --revision 7c6bf9a2faef35209646cd7f1569fae2b2394a00
Run at home

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
be2ff596e067105d65140db726c7497eae60907d3fd07cf6d4a663c8c1bc76a6
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: unsloth <huggingface.co/unsloth>Newsgroups: alt.freeweights.smollmSubject: SmolLM2-360M-InstructDate: 2026-11-15Commit: 7c6bf9aSigned: 2DC28CC7B26A283B ✓
Upstream
unsloth/SmolLM2-360M-Instruct
Pinned commit
7c6bf9a2faef35209646cd7f1569fae2b2394a00
Manifest
SmolLM2-360M-Instruct.json · .minisig
Manifest sha256
40c0621b60c3af0bf8ba64acb5c875ca59b58ba92fa75c099f108dcf4bea2345
Signature
minisign, Ed25519, key 2DC28CC7B26A283B
Created
2026-11-15 03:28 UTC
Generator
freeweights-manifest/0.1.0
Takedowns
None.

How to verify

$ curl -O https://freeweights.allternit.com/manifests/unsloth/SmolLM2-360M-Instruct.json $ curl -O https://freeweights.allternit.com/manifests/unsloth/SmolLM2-360M-Instruct.json.minisig $ minisign -Vm SmolLM2-360M-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

HuggingFaceTB/SmolLM2-360M-Instruct · this model is a finetune of it

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

Get it
Download
$ HF_ENDPOINT=https://freeweights.allternit.com hf download unsloth/SmolLM2-360M-Instruct
Open in Freeweights Studio

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

Signed manifest
minisign, key 2DC28CC7B26A283B. SmolLM2-360M-Instruct.json. Provenance. Takedown history: none.
Source
huggingface.co/unsloth/SmolLM2-360M-Instruct

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