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

SmolLM2-360M

Date: 2026-11-15Commit: 509ecc7Signed: 2DC28CC7B26A283B ✓

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

362M params728MBSmolLM2-360Msafetensorspermissive
FactsParams362MSize728 MBFormatssafetensorsTasktext generationLicenseApache-2.0From sourcepermissive
$ fw get unsloth/SmolLM2-360M
# manifest sha256 c9e4079a8646… · 728 MB · 11 files
$ fw verify ./SmolLM2-360M unsloth/SmolLM2-360M
From sourceHosted (signed)unsloth/SmolLM2-360MLast check: 2026-11-15 03:29 UTC
Run at homeGet help

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

Fine-tune of SmolLM2-360M.

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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

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 03:29 UTCpassed

Model card

From the publisher at commit 509ecc7. 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#

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.md4.54 KB5498cc12c1a8a910bd4f4e98c129a6b0fd46b10072f5e01609b06282f56dd377
added_tokens.json29 B5a7038c26cb1d019b0258d86889308341cf8c0166978b05f5996be953bb69c9e
config.json802 B7cda3ed92b511584a4e124735812d60b414085dc0a3d03b8fe5715e1d6a9a95b
generation_config.json158 Bbdf0e6ee437433ed0a4f45e681ea4a11ee1b5345b53d94fdebe3c1255395e00e
merges.txt466 KB0b54e8aa4e53d5383e2e4bc635a56b43f9647f7b13832d5d9ecd8f82dac4f510
model.safetensors724 MB8967eed282d670509671ec30189a673d97223ad30a0e222496b8ea1c203353f8
special_tokens_map.json742 Bd7e4d3a4f4c5e5e98d2926dfbb26f5d16d9824e0f8344830824ea424dfcc79eb
tokenizer.json3.52 MB66bfc9a0d05ad54eef8e1f906d77fd37663e8a51eb1c56b44d2e4227448f91fb
tokenizer_config.json3.89 KB438c85898efa922b34eef16512ee7d4bf9f888ccf99377e5edfcdde512d496be
vocab.json801 KB82b84012e3add4d01d12ba14442026e49b8cbbaead1f79ecf3d919784f82dc79
VersionsEach time the pinned upstream commit or file list changed in this repo. Newest first.
Upstream commitDateContents
509ecc708d pinned now2026-11-15 03:29 UTC11 files · 728 MB

Use it

$ fw get unsloth/SmolLM2-360M
# manifest sha256 c9e4079a8646… · 728 MB · 11 files
$ fw verify ./SmolLM2-360M unsloth/SmolLM2-360M
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.json --dir ./SmolLM2-360M $ python3 fw.py verify ./SmolLM2-360M ./unsloth__SmolLM2-360M.json
hfThe Hugging Face CLI with one setting. Same repo id.
$ HF_ENDPOINT=https://freeweights.allternit.com hf download unsloth/SmolLM2-360M --revision 509ecc708d9d2bcfd99f3537122b047d6559f791 --local-dir ./SmolLM2-360M
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", revision="509ecc708d9d2bcfd99f3537122b047d6559f791") model = AutoModelForCausalLM.from_pretrained("unsloth/SmolLM2-360M", revision="509ecc708d9d2bcfd99f3537122b047d6559f791", device_map="auto")
vLLMServe an OpenAI-compatible API.
$ HF_ENDPOINT=https://freeweights.allternit.com vllm serve unsloth/SmolLM2-360M --revision 509ecc708d9d2bcfd99f3537122b047d6559f791
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
5498cc12c1a8a910bd4f4e98c129a6b0fd46b10072f5e01609b06282f56dd377
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: SmolLM2-360MDate: 2026-11-15Commit: 509ecc7Signed: 2DC28CC7B26A283B ✓
Upstream
unsloth/SmolLM2-360M
Pinned commit
509ecc708d9d2bcfd99f3537122b047d6559f791
Manifest
SmolLM2-360M.json · .minisig
Manifest sha256
c9e4079a86467c9e4480f20d8c6242c8a557ec7e404cd0dbf31877208f431175
Signature
minisign, Ed25519, key 2DC28CC7B26A283B
Created
2026-11-15 03:29 UTC
Generator
freeweights-manifest/0.1.0
Takedowns
None.

How to verify

$ curl -O https://freeweights.allternit.com/manifests/unsloth/SmolLM2-360M.json $ curl -O https://freeweights.allternit.com/manifests/unsloth/SmolLM2-360M.json.minisig $ minisign -Vm SmolLM2-360M.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 · 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
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.json. Provenance. Takedown history: none.
Source
huggingface.co/unsloth/SmolLM2-360M

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