Trl Internal Testing · Tiny Lfm2ForCausalLM

tiny-Lfm2ForCausalLM

Unverified · community-discovered, not yet reviewed

tiny-Lfm2ForCausalLM is a discovered model from public model catalogues. Badgr builds a GPU serving profile from source metadata, estimated VRAM, context length, and available execution routes.

Last validated or meaningfully updated: Dynamic source discovery

ChatFine-tunable

Availability

Not yet Badgr AI API

Not currently validated

Dedicated endpoint

Available through Badgr

Custom GPU deployment

Available through Badgr

Deployment profile

Architecture
Source metadata pending
Licence
Check model card
Minimum VRAM
~18GB
Context
Source dependent

Recommended: RTX 4090 24GB. VRAM is an estimate and increases with context, cache, concurrency, and runtime overhead.

Model identity

Updated
28 days ago
HuggingFace revision
119d70b9bb

Popularity and trust

Downloads (last month)

119.2K

Likes

0

Spaces using this model

0

Files and formats

Weight formats

Safetensors

Repository files

9

Chat template

Available

GPU deployment scenarios

Estimated from parameter count and quantisation. Will switch to “Verified by Badgr” once a real run backs a tier.

Testing

RTX 4090 24GB

Short context, low concurrency

Small production

L40S 48GB

8K context, 1-4 concurrent requests

Higher throughput

A100 80GB

32K context, continuous batching

Large production

RTX 4090 24GB

Higher concurrency

Estimated — multimodal inputs, long context, and concurrency all increase real VRAM use beyond this estimate.

Also runs well on L40S 48GB, A100 40GB. Available in United States, Europe.

Serving compatibility

RuntimeStatusNotes
vLLMEstimatedUsed for Badgr dedicated endpoints
TransformersDeclared by sourceBasic fallback
llama.cppRequires GGUF conversionNo GGUF weights found in repo
SGLangUnknownNot evaluated
TensorRT-LLMUnknownConversion may be required
TGIUnknownNot evaluated

Ready-to-run Badgr configurations

Quick test

badgr serve trl-internal-testing/tiny-Lfm2ForCausalLM --max-cost 2

Dedicated endpoint command

badgr serve trl-internal-testing/tiny-Lfm2ForCausalLM --gpu RTX 4090 --max-cost 10

Advanced configuration (defaults to automatic)

  • Runtime
  • Quantisation
  • GPU and GPU count
  • Context length
  • Maximum concurrency
  • Region
  • Maximum hourly spend
  • Persistent or capped runtime

Estimated pricing

Provider estimate: cold start

2–5 min

Provider estimate: endpoint cost

$0.17 – $0.17/hr

Idle cost

$0 when stopped

Per-token throughput cost is not shown here: Badgr has not benchmarked this model yet, and this page does not display figures it cannot back with real data.

Recommended Badgr routes

RTX 4090 24GB · United States

Available

from $0.17/hr

Best for

ComfyUI, Batch Inference, Qwen 2.5 7B Instruct

Startup: 2–5 min

Reliability: Standard

Last checked: just now

RTX 4090 24GB · United States

Available

from $0.17/hr

Best for

ComfyUI, Batch Inference, Qwen 2.5 7B Instruct

Startup: 2–5 min

Reliability: Standard

Last checked: just now

RTX 4090 24GB · United States

Available

from $0.17/hr

Best for

ComfyUI, Batch Inference, Qwen 2.5 7B Instruct

Startup: 2–5 min

Reliability: Standard

Last checked: just now

RTX 4090 24GB · Europe

Available

from $0.17/hr

Best for

ComfyUI, Batch Inference, Qwen 2.5 7B Instruct

Startup: 2–5 min

Reliability: Standard

Last checked: just now

RTX 4090 24GB · Europe

Available

from $0.17/hr

Best for

ComfyUI, Batch Inference, Qwen 2.5 7B Instruct

Startup: 2–5 min

Reliability: Standard

Last checked: just now

RTX 4090 24GB · Europe

Available

from $0.17/hr

Best for

ComfyUI, Batch Inference, Qwen 2.5 7B Instruct

Startup: 2–5 min

Reliability: Standard

Last checked: just now

Known limitations

  • Source-discovered pages use best-effort metadata until the model is reviewed.
  • Licence, gated access, runner compatibility, and exact memory use should be checked before production deployment.

Related troubleshooting