Hugging Face Transformers
An open-source library for building and working with pre-trained transformer models for natural language, vision, audio, and multimodal tasks.
- Also known as
- hugging-face-transformers, Hugging Face
Available worldwide
What is Hugging Face Transformers?
A framework for machine learning that provides pre-trained transformer models and tools for both training and inference across text, vision, audio, and multimodal modalities. Designed to work with PyTorch and support a wide range of ML tasks.
Hugging Face Transformers pricing
Plans, per-tier features and add-ons, dated and linked to live pricing. Pricing changes often; always verify at source before you rely on it.
PRO at $9/month, Team from $20/user/month, storage from $8/TB/month, compute starting at $0.033/hour. Free tier available.
PRO
Personal account upgrade
- Private storage
- 20× included inference credits
- Host ZeroGPU, Gradio & Docker Spaces
- 8× ZeroGPU quota
- Highest queue priority
- PRO badge
Team
Growing teams
- Single Sign-On
- Regions
- Priority Support
- Audit Logs
- Resource Groups
- Access 45,000+ models via unified API
Enterprise
Contact salesCustom onboarding and enterprise features
- Enterprise-grade security
- Access controls
- Dedicated support
- Custom configuration
Add-ons
- Storage$12 per TB/month + $8 per TB/month + $10 per TB/month
- Spaces Hardware$0.03 per hour + $0.40 per hour + $0.80 per hour + $23.50 per hour
- Inference Endpoints$0.03 per hour + $4.50 per hour + $74 per hour
What Hugging Face Transformers does
The capabilities that matter for nlp apis, normalised so it lines up with every alternative. “-” means we haven't confirmed it, not that it's missing.
- Custom model training
- ✓
- Domain specific models
- ✓
- Deployment model
- Self hostable
- Batch processing
- -
- Real time latency
- -
- Embeddings endpoint
- -
- Data residency EU
- -
- Open source
- ✓
- Pricing model
- Open source self host
Platform & deployment
Independently observed- CLI
- Self-hosted
Integrations (6)
Independently observed- PyTorch•
- Kaggle
- AWS
- Azure
- GCP
- NVIDIA DGX Cloud
Hugging Face Transformers FAQ
Common questions about Hugging Face Transformers, answered from independent, dated evidence.
What is Hugging Face Transformers?
A community-driven hub where developers can create, discover, and collaborate on AI models, datasets, and applications with integrated compute resources and deployment capabilities. It is indexed under NLP Apis.
Source: https://huggingface.co/pricing
Is Hugging Face Transformers free?
Hugging Face Transformers offers a free tier, so you can start without paying. Paid plans start at $9 per month. Prices are published openly on the vendor's own pricing page. Pricing changes often, so verify at source before relying on it.
Source: https://huggingface.co/pricing
What platforms does Hugging Face Transformers support?
Hugging Face Transformers supports the web and a command-line interface. Platforms we have not confirmed are simply not listed here rather than ruled out.
Source: https://huggingface.co/pricing
Can Hugging Face Transformers be self-hosted?
We have only confirmed a cloud / SaaS deployment for Hugging Face Transformers, so it appears to be vendor-hosted. If a self-hosted option exists we have not found it documented publicly.
Source: https://huggingface.co/pricing
What does Hugging Face Transformers integrate with?
We have confirmed 5 integrations for Hugging Face Transformers, including Kaggle, AWS, Azure, GCP and NVIDIA DGX Cloud. This is what we could verify from public sources, so the vendor may support others we have not indexed.
Source: https://huggingface.co/pricing
What security certifications does Hugging Face Transformers have?
We have independently confirmed GDPR for Hugging Face Transformers. Certifications we do not list are ones we have not been able to verify from public sources, which is not the same as Hugging Face Transformers not holding them. Always confirm compliance directly before you rely on it.
Source: https://huggingface.co/blog/security-incident-july-2026
Hugging Face Transformers alternatives
Other nlp apis we track, ranked by the same independent score.
- CohereEnterprise AI that you fully control and deploy according to your requirementsmedium · 55%
- NLTKlow · 25%
- TextRazorNLP API for extracting meaning and understanding from textlow · 24%
- spaCyProduction-grade Python library for natural language processinglow · 39%
- Amazon ComprehendManaged natural language processing service for analyzing text and extracting structured insightsmedium · 54%
- Stanford CoreNLPA Java library for extracting linguistic information from textlow · 34%
Compare Hugging Face Transformers
Side by side against other nlp apis, attribute by attribute, with a source on every value.
The vioscaleAI score: one lens on the evidence
Not user reviews and not a paid placement: a confidence-weighted blend of the independent signals below (adoption, activity, security posture, and more), which you can sort and re-weight yourself. Vendors can correct their listing but can never move their rank, and stars are weighted low as a vanity metric. It is one way to read the evidence for Hugging Face Transformers, not the verdict.
| Signal | Score | Weight | Contribution | Evidence |
|---|---|---|---|---|
| Capabilities | 58 | 0.08 | 4.6 | ✓ |
| Integrations | 22 | 0.05 | 1.2 | ✓ |
| Stars | 0 | 0.05 | 0.0 | - |
| Dependent projects | 0 | 0.05 | 0.0 | - |
| Development activity | 0 | 0.14 | 0.0 | - |
| Release cadence | 0 | 0.08 | 0.0 | - |
| Security posture | 10 | 0.12 | 0.0 | - |
| Package downloads | 0 | 0.04 | 0.0 | - |
| Security score | 0 | 0.05 | 0.0 | - |
| Developer Q&A activity | 0 | 0.14 | 0.0 | - |
Computed . Re-weight it by intent, or see the full method.
All data & sourcesshow ↓
Every value we hold, with its source, retrieval date, and confidence. This is the evidence behind the score: don't trust it, verify it.
Content
| Attribute | Value | Evidence |
|---|---|---|
| Faq | 6 items | mediumsource · 2026-09-10 · 62% |
Features
| Attribute | Value | Evidence |
|---|---|---|
| Capabilities | Open source: Yes · Pricing model: open-source-self-host · Deployment model: self-hostable · Custom model training: Yes · Domain specific models: Yes | mediumsource · 2026-09-16 · 60% |
Integrations
| Attribute | Value | Evidence |
|---|---|---|
| Count | 5 | mediumsource · 2026-08-19 · 60% |
Market
| Attribute | Value | Evidence |
|---|---|---|
| Availability | PrimaryMarkets: … · AvailabilityScope: global · AvailableCountries: … · NotAvailableCountries: … | highsource · 2026-08-19 · 75% |
Pricing
Security
Is Hugging Face Transformers the right choice for you?
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