Text Generation
Transformers
Safetensors
OpenPeerLLM
English
Arabic
riemann_openpeer
amd
ntk
code
fsdp
rocm
coding
mi325x
decoder
code gen
directml
openpeer
ryzen-ai
reasoning
rewriting
multimodal
paraphrase
prerelease
ntk-trainer
growth-ladder
style-transfer
text-rewriting
riemann-computing
progressive-growth
custom_code
Eval Results (legacy)
Instructions to use OpenPeerAI/My-Name-is-Riemann-Prerelease with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenPeerAI/My-Name-is-Riemann-Prerelease with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="OpenPeerAI/My-Name-is-Riemann-Prerelease", trust_remote_code=True)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("OpenPeerAI/My-Name-is-Riemann-Prerelease", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use OpenPeerAI/My-Name-is-Riemann-Prerelease with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "OpenPeerAI/My-Name-is-Riemann-Prerelease" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OpenPeerAI/My-Name-is-Riemann-Prerelease", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/OpenPeerAI/My-Name-is-Riemann-Prerelease
- SGLang
How to use OpenPeerAI/My-Name-is-Riemann-Prerelease with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "OpenPeerAI/My-Name-is-Riemann-Prerelease" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OpenPeerAI/My-Name-is-Riemann-Prerelease", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "OpenPeerAI/My-Name-is-Riemann-Prerelease" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OpenPeerAI/My-Name-is-Riemann-Prerelease", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use OpenPeerAI/My-Name-is-Riemann-Prerelease with Docker Model Runner:
docker model run hf.co/OpenPeerAI/My-Name-is-Riemann-Prerelease
File size: 3,145 Bytes
db3982a 4b08de9 db3982a | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 | param(
[string]$NodeIp = (Get-Content "$env:RIEMANN_ROOT\cloud_state\node_ip.txt").Trim(),
[string]$LocalRoot = $env:RIEMANN_ROOT,
[string]$RemoteRoot = "/workspace/RiemannModel",
[int]$PollSeconds = 300
)
$ErrorActionPreference = "Continue"
$node = "root@$NodeIp"
function Log($m) { "$(Get-Date -Format 'yyyy-MM-dd HH:mm:ss') [mirror] $m" }
New-Item -ItemType Directory -Force -Path "$LocalRoot\checkpoints", "$LocalRoot\ntk_controllers", "$LocalRoot\cloud_logs" | Out-Null
function Pull-Small {
cmd /c "ssh $node ""tar -C $RemoteRoot -cf - ntk_controllers logs"" | tar -xf - -C ""$LocalRoot\_incoming""" 2>$null
if (Test-Path "$LocalRoot\_incoming\ntk_controllers") { Copy-Item "$LocalRoot\_incoming\ntk_controllers\*" "$LocalRoot\ntk_controllers\" -Force }
if (Test-Path "$LocalRoot\_incoming\logs") { Copy-Item "$LocalRoot\_incoming\logs\*" "$LocalRoot\cloud_logs\" -Force }
}
function Pull-Stage($stage) {
Log "pulling $stage ..."
$dest = "$LocalRoot\checkpoints"
$t = [Diagnostics.Stopwatch]::StartNew()
cmd /c "ssh $node ""tar -C $RemoteRoot/checkpoints -cf - $stage"" | tar -xf - -C ""$dest"""
$t.Stop()
$remote = ssh $node "cd $RemoteRoot/checkpoints/$stage && sha256sum *.safetensors *.json 2>/dev/null"
$ok = $true
foreach ($line in $remote) {
if ($line -match '^([0-9a-f]{64})\s+\*?(.+)$') {
$rsha = $matches[1]; $name = $matches[2].Trim()
$local = Join-Path "$dest\$stage" $name
if (-not (Test-Path $local)) { Log "MISSING $name"; $ok = $false; continue }
$lsha = (Get-FileHash -Algorithm SHA256 $local).Hash.ToLower()
if ($lsha -ne $rsha) { Log "SHA MISMATCH $name"; $ok = $false }
}
}
$gb = [math]::Round((Get-ChildItem "$dest\$stage" -File | Measure-Object Length -Sum).Sum / 1GB, 2)
if ($ok) {
Set-Content "$dest\$stage\.mirrored" (Get-Date -Format o)
Log "$stage mirrored and verified: $gb GB in $([math]::Round($t.Elapsed.TotalMinutes,1)) min"
} else {
Log "$stage verification FAILED; will retry next cycle"
Remove-Item "$dest\$stage\.mirrored" -ErrorAction SilentlyContinue
}
}
New-Item -ItemType Directory -Force -Path "$LocalRoot\_incoming" | Out-Null
Log "mirroring $node -> $LocalRoot every $PollSeconds s"
while ($true) {
try {
Pull-Small
$done = ssh $node "ls $RemoteRoot/checkpoints/*/.rung_done 2>/dev/null"
foreach ($m in $done) {
if ($m -match 'checkpoints/([^/]+)/\.rung_done') {
$stage = $matches[1]
if (-not (Test-Path "$LocalRoot\checkpoints\$stage\.mirrored")) { Pull-Stage $stage }
}
}
$allDone = ssh $node "grep -c 'GATE: ALL DONE' $RemoteRoot/logs/bootstrap.log 2>/dev/null"
if ("$allDone" -match '^[1-9]') {
Pull-Small
Log "bootstrap reports ALL DONE and every finished rung is mirrored; exiting"
break
}
} catch { Log "cycle error: $($_.Exception.Message)" }
Start-Sleep $PollSeconds
}
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