Updated 7 h ago · first seen 11 Sept 2026
model_01M294YAD6M53FSE331J5Z0WZK
Overview
Identity
Identity block not returned by the API for this entity.
Openness
Openness not classified yet — no sourced evidence to place this model in the ontology.
Key facts
- Release date
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 13 h agomedium
- Model card
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 13 h agomedium
Architecture
- Architecture
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 13 h agomedium
- Model type
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 13 h agomedium
- Parameters
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 13 h agomedium
- Weights dtype
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 13 h agomedium
- File size
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 13 h agomedium
- Library name
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 13 h agomedium
- Hugging Face repo
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 13 h agomedium
Capabilities
Modalities
Modalities unavailable.
Capabilities
Tool calling
Unavailable
Structured output
Unavailable
Reasoning
Unavailable
Vision
Unavailable
Audio
Unavailable
Fine-tuning available
Unavailable
No capability flags have been observed from a source yet — we do not infer them.
- Languages
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 13 h agomedium
Hardware fit37
Assumptions (6)
- Estimated, not measured: weights = parameters × bytes/param × 1.15 runtime overhead.
- bytes/param: 4bit = 0.5, 8bit = 1.0, fp16 = 2.0 (uniform quantization, no per-layer exceptions).
- KV cache approximated at 0.5 GB per 8 192 tokens of context, independent of architecture (GQA/MLA models need less).
- A model 'fits' when the estimate is at most the device memory minus 2 GB reserved for the OS and framework.
- Mixture-of-experts models are estimated on total parameters (all experts must be resident); active parameters are ignored.
- Device memory uses the largest configuration when several are listed (e.g. Apple silicon tiers).
Papers3
- arXiv:2304.01373Active35
- arXiv:2101.00027Active35
- arXiv:2201.07311Active35
Datasets1
- EleutherAI/pileActive35
Timeline1
Full timeline →Change history19
Viewing AI Atlas as of 1 Jan 2024 — attributes exactly as the atlas knew them on that day; later corrections are not shown.
Back to today →pythia-70m was not yet in AI Atlas on 1 Jan 2024
Release daterelease_date1
Opennessopenness1
Licenselicense1
Architecturearchitecture1
Parametersparameter_count1
Languageslanguages1
File sizefile_size_gb1
Hugging Face repohf_repo1
Model cardmodel_card_url1
Downloadsmetric.downloads1
Likesmetric.likes1
Datasetsdatasets1
Gatedgated1
Last modifiedlast_modified1
Library namelibrary_name1
Downloads all timemetric.downloads_all_time1
Model typemodel_type1
Weights dtypeweights_dtype1
Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →
Provenance
Attributed facts
19
Source tiers
T219
Freshest observation
7 h ago
Conflicts
None
Source documents 3
Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.
Data quality (53/100) measures how well AI Atlas knows this entity — completeness, primary-source ratio, freshness, conflicts — never how good the model is. Methodology →