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Healthcare / Life Science·custom_container·mit·Added May 22, 2026

ESM-2 650M Protein Embeddings

ESM-2 650M is a non-clinical protein language model for sequence representation learning.

protein_sequence→embedding, json
life-sciencebiologyproteinembedding+5
Try in playground ↓Deploy Serverless ↓Open Hugging Face model ↗API docs
Recommended targetB300 in uk-south1Picked from the fastest verified GPU/region for this model version. Playground and API docs links are pinned to this route.
Context window
1024
VRAM needed
1.9 GB

Observed working set on a supported GPU.

API route
POST /v1/inference/facebook-esm-2-650m
Weights dtype
BF16
Pulled image size
4.6 GB

After the last request a backend stays warm on its GPU for about 15 minutes, then frees the GPU. The next request triggers a fresh cold start.

Status
cold
Not running.
API target

facebook-esm-2-650m version hf-08e4846-wrapper-20260427-timing on B300 in uk-south1

POST to the native route with the shown model field; the playground below generates a full payload.

Open docsTry target
API route
/v1/inference/facebook-esm-2-650m
HTTP method
POST
Model field
facebook-esm-2-650m
Version field
model_version: hf-08e4846-wrapper-20260427-timing
GPU field
gpu_type: B300
Region field
region: uk-south1
  1. 1Verify targetRuns the auth guard and selected endpoint/model/routing check.
  2. 2Validate targetConfirm the selected GPU or region is still verified, or print copyable best-target exports.
  3. 3Estimate runValidate warm and first-cold request cost before prewarming or first traffic.
  4. 4Check runtimeConfirm whether the selected version is warm or starting.
  5. 5Prewarm targetStart the selected version on its pinned GPU or region before latency-sensitive traffic.
  6. 6Open docsUse the selected target snippets for the first request.Open docs
One-block API check

Terminal-ready smoke test for this selected target.

View command
set -euo pipefail
# Forge API smoke test
# Forge selected target: route=/v1/models/facebook-esm-2-650m/inference-routes model=facebook-esm-2-650m version=hf-08e4846-wrapper-20260427-timing gpu=B300 region=uk-south1
FORGE_API_BASE=${FORGE_API_BASE:-'https://YOUR_FORGE_HOST'}
case "${FORGE_API_KEY:-}" in
  ""|replace-with-your-forge-api-key)
    echo 'Set FORGE_API_KEY to a real Forge API key before running this snippet; browser SSO sessions are not sent to copied curl or SDK clients.' >&2
    exit 1
    ;;
esac
forge_api_url() {
  endpoint="$1"
  base="${FORGE_API_BASE%/}"
  case "$base:$endpoint" in
    */v1:/v1|*/v1:/v1/*|*/v1:/v1\?*) printf '%s%s\n' "$base" "${endpoint#/v1}" ;;
    *) printf '%s%s\n' "$base" "$endpoint" ;;
  esac
}
curl -sS --fail-with-body "$(forge_api_url '/v1/models/facebook-esm-2-650m/inference-routes?model_version=hf-08e4846-wrapper-20260427-timing&gpu_type=B300&region=uk-south1')" \
  --max-time "${FORGE_REQUEST_TIMEOUT_SECONDS:-600}" \
  -H "Authorization: Bearer ${FORGE_API_KEY}" | \
python3 -m json.tool
Client fit

Native route check · Best for model-specific payloads; run the route check first, then copy the schema-specific request from the playground.

Routing pinned

Copied snippets include gpu_type and region, so the first request targets this verified GPU and region. Remove those fields to let Forge choose another compatible target.

Target availability

8 free GPUs · Live capacity for B300 in uk-south1.

Request URL
https://YOUR_FORGE_HOST/v1/inference/facebook-esm-2-650m
Authentication

Client auth: Set FORGE_API_KEY to a real Forge API key before running copied curl, fetch, or SDK snippets. Browser SSO only authenticates this web session.

Open Account
Authorization: Bearer $FORGE_API_KEY
Pinned setup
export FORGE_API_BASE='https://YOUR_FORGE_HOST'
export FORGE_API_KEY="${FORGE_API_KEY:-replace-with-your-forge-api-key}"
export FORGE_REQUEST_TIMEOUT_SECONDS="${FORGE_REQUEST_TIMEOUT_SECONDS:-600}"
export FORGE_API_ROUTE='/v1/inference/facebook-esm-2-650m'
export MODEL_OR_FAMILY_SLUG='facebook-esm-2-650m'
export FORGE_MODEL_VERSION='hf-08e4846-wrapper-20260427-timing'
export FORGE_GPU_TYPE='B300'
export FORGE_REGION='uk-south1'
Project .env

Copy these values into a local .env file when moving the selected target into an app or SDK client.

# Forge selected target: route=/v1/inference/facebook-esm-2-650m model=facebook-esm-2-650m version=hf-08e4846-wrapper-20260427-timing gpu=B300 region=uk-south1
FORGE_API_BASE="https://YOUR_FORGE_HOST"
FORGE_API_ROUTE="/v1/inference/facebook-esm-2-650m"
FORGE_API_KEY="replace-with-your-forge-api-key"
FORGE_REQUEST_TIMEOUT_SECONDS="600"
MODEL_OR_FAMILY_SLUG="facebook-esm-2-650m"
FORGE_MODEL_VERSION="hf-08e4846-wrapper-20260427-timing"
FORGE_GPU_TYPE="B300"
FORGE_REGION="uk-south1"
Project .gitignore

Add these rules before replacing the placeholder API key so local Forge secrets stay out of commits while .env.example can remain tracked.

# Forge local API secrets
.env
.env.*
!.env.example
Preflight URLs and commands
Run estimate URL
https://YOUR_FORGE_HOST/v1/models/facebook-esm-2-650m/run-estimate?model_version=hf-08e4846-wrapper-20260427-timing&gpu_type=B300&region=uk-south1
Selected target reliability
set -euo pipefail # Forge selected target: route=/v1/inference/facebook-esm-2-650m model=facebook-esm-2-650m version=hf-08e4846-wrapper-20260427-timing gpu=B300 region=uk-south1 FORGE_API_BASE=${FORGE_API_BASE:-'https://YOUR_FORGE_HOST'} export MODEL_OR_FAMILY_SLUG=${MODEL_OR_FAMILY_SLUG:-'facebook-esm-2-650m'} export FORGE_MODEL_VERSION=${FORGE_MODEL_VERSION:-'hf-08e4846-wrapper-20260427-timing'} export FORGE_GPU_TYPE=${FORGE_GPU_TYPE:-'B300'} export FORGE_REGION=${FORGE_REGION:-'uk-south1'} case "${FORGE_API_KEY:-}" in ""|replace-with-your-forge-api-key) echo 'Set FORGE_API_KEY to a real Forge API key before running this snippet; browser SSO sessions are not sent to copied curl or SDK clients.' >&2 exit 1 ;; esac forge_api_url() { endpoint="$1" base="${FORGE_API_BASE%/}" case "$base:$endpoint" in */v1:/v1|*/v1:/v1/*|*/v1:/v1\?*) printf '%s%s\n' "$base" "${endpoint#/v1}" ;; *) printf '%s%s\n' "$base" "$endpoint" ;; esac } reliability_path="$(python3 -c 'import os from urllib.parse import quote, urlencode model = os.environ.get("MODEL_OR_FAMILY_SLUG", "").strip() if not model: raise SystemExit("Set MODEL_OR_FAMILY_SLUG from search or route finder output before checking reliability.") params = {} model_version = os.environ.get("FORGE_MODEL_VERSION", "").strip() if model_version: params["model_version"] = model_version gpu_type = os.environ.get("FORGE_GPU_TYPE", "").strip() if gpu_type: params["gpu_type"] = gpu_type region = os.environ.get("FORGE_REGION", "").strip() if region: params["region"] = region path = "/v1/models/" + quote(model, safe="") + "/reliability" if params: path += "?" + urlencode(params) print(path)')" curl -sS --fail-with-body "$(forge_api_url "$reliability_path")" \ --max-time "${FORGE_REQUEST_TIMEOUT_SECONDS:-600}" \ -H "Authorization: Bearer ${FORGE_API_KEY}" | \ python3 -c 'import json, shlex, sys payload = json.load(sys.stdin) print( f"{payload.get('\''slug'\'')} reliability={payload.get('\''reliability_status'\'')} " f"supported={payload.get('\''supported_rows'\'', 0)}/{payload.get('\''total_rows'\'', 0)}" ) filters = payload.get("filters") or {} if filters: print("filters: " + ", ".join(f"{key}={value}" for key, value in filters.items())) def describe_target(target): details = [] request_ms = target.get("request_ms_p50") or target.get("request_ms") if request_ms is not None: details.append(f"p50={request_ms}ms") warm_cost = target.get("estimated_warm_request_cost_usd") if warm_cost is not None: details.append(f"warm_cost_usd={warm_cost}") elif target.get("cost_per_gpu_hour_usd") is not None: details.append(f"gpu_hour_usd={target['\''cost_per_gpu_hour_usd'\'']}") success_rate = target.get("observed_success_rate") if isinstance(success_rate, (int, float)): details.append(f"success={success_rate:.0%}") return ", ".join(details) or target.get("status") or "supported" exports = {} for label, key in ( ("fastest supported", "fastest_supported_target"), ("lowest-cost supported", "lowest_cost_supported_target"), ): target = payload.get(key) or {} gpu_type = target.get("gpu_type") if not gpu_type: continue identity = (str(gpu_type), str(target.get("region") or "")) exports.setdefault(identity, {"labels": [], "target": target})["labels"].append(label) if not exports: print("No supported GPU/region target returned.", file=sys.stderr) print(json.dumps({ "status_counts": payload.get("status_counts", {}), "failure_reason_counts": payload.get("failure_reason_counts", {}), }, indent=2)) raise SystemExit(1) for (gpu_type, region), entry in exports.items(): assignments = [f"FORGE_GPU_TYPE={shlex.quote(gpu_type)}"] if region: assignments.append(f"FORGE_REGION={shlex.quote(region)}") labels = " + ".join(entry["labels"]) details = describe_target(entry["target"]) print(f"export {'\'' '\''.join(assignments)} # {labels}: {details}")'
Runtime status URL
https://YOUR_FORGE_HOST/v1/model-families/facebook-esm-2-650m/status?version=hf-08e4846-wrapper-20260427-timing
Runtime warmup command
set -euo pipefail # Forge selected target: route=/v1/inference/facebook-esm-2-650m model=facebook-esm-2-650m version=hf-08e4846-wrapper-20260427-timing gpu=B300 region=uk-south1 FORGE_API_BASE=${FORGE_API_BASE:-'https://YOUR_FORGE_HOST'} export MODEL_OR_FAMILY_SLUG=${MODEL_OR_FAMILY_SLUG:-'facebook-esm-2-650m'} export FORGE_MODEL_VERSION=${FORGE_MODEL_VERSION:-'hf-08e4846-wrapper-20260427-timing'} export FORGE_GPU_TYPE=${FORGE_GPU_TYPE:-'B300'} export FORGE_REGION=${FORGE_REGION:-'uk-south1'} export FORGE_KEEP_WARM=${FORGE_KEEP_WARM:-false} case "${FORGE_API_KEY:-}" in ""|replace-with-your-forge-api-key) echo 'Set FORGE_API_KEY to a real Forge API key before running this snippet; browser SSO sessions are not sent to copied curl or SDK clients.' >&2 exit 1 ;; esac forge_api_url() { endpoint="$1" base="${FORGE_API_BASE%/}" case "$base:$endpoint" in */v1:/v1|*/v1:/v1/*|*/v1:/v1\?*) printf '%s%s\n' "$base" "${endpoint#/v1}" ;; *) printf '%s%s\n' "$base" "$endpoint" ;; esac } runtime_start_path="$(python3 -c 'import os from urllib.parse import quote model = os.environ.get("MODEL_OR_FAMILY_SLUG", "").strip() if not model: raise SystemExit("Set MODEL_OR_FAMILY_SLUG from the model picker output") print("/v1/model-families/" + quote(model, safe="") + "/start")')" python3 -c 'import json, os def env_value(name): value = os.environ.get(name, "").strip() return value or None payload = {} version = env_value("FORGE_MODEL_VERSION") if version: payload["version"] = version gpu_type = env_value("FORGE_GPU_TYPE") if gpu_type: payload["gpu_type"] = gpu_type region = env_value("FORGE_REGION") if region: payload["region"] = region keep_warm = env_value("FORGE_KEEP_WARM") payload["run_until_stopped"] = (keep_warm or "").lower() in {"1", "true", "yes", "on"} print(json.dumps(payload))' | \ curl -sS --fail-with-body "$(forge_api_url "$runtime_start_path")" \ --max-time "${FORGE_REQUEST_TIMEOUT_SECONDS:-600}" \ -X POST \ -H "Authorization: Bearer ${FORGE_API_KEY}" \ -H "Content-Type: application/json" \ -d @- | \ python3 -c 'import json, sys payload = json.load(sys.stdin) slug = payload.get("slug") or "runtime" gpu_type = payload.get("gpu_type") or "scheduler-selected GPU" region = payload.get("region") or "scheduler-selected region" startup_ms = payload.get("startup_ms") state = "cold-started" if payload.get("was_cold_start") else "already warm" suffix = f"; startup_ms={startup_ms}" if startup_ms is not None else "" print(f"{slug} {state} on {gpu_type} in {region}{suffix}; keep_warm={payload.get('\''keep_warm'\'')}")'

GPU performance

Pick a verified target for repeatable runs. Failed or pending details appear on the status hover.

Try selected target
Runs on · HF 08e4846 via Forge life-science wrapper
0.7 B params · weights BF16 · floor 16 GB
Target readiness

7 verified targets

7/8 verified0 awaiting probe1 unavailable
Fastest verified
B300 in uk-south1
Use in playground

Lowest warm model time among verified targets: 13 ms p50 warm model time across 11 samples.

Model time
13 msp50 warm model time
p95 14 ms · p99 15 ms · 11 samples
Cold start
3m 43s
Most affordable
L40S in eu-north1
Use in playground

Lowest estimated GPU price among verified targets: $1.82/GPU-hr; 23 ms p50 warm model time across 11 samples.

Model time
23 msp50 warm model time
p95 28 ms · p99 30 ms · 11 samples
Cold start
1m 5s
GPURegionStatusVRAMCold startModel timeRelativeEst. $/GPU-hrTarget
B200us-central1works2.1 GB3m 55s14 msp50 warm model time
p99 15 ms · 11 samples
93% · -7%$7.15Use in playground
B300fastestuk-south1works2.1 GB3m 43s13 msp50 warm model time
p95 14 ms · p99 15 ms · 11 samples
100%$7.85Use in playground
H100eu-north1works2.0 GB4m 20s14 msp50 warm model time
10 samples
93% · -7%$3.85Use in playground
H200eu-north1works2.0 GB3m 52s14 msp50 warm model time
p95 15 ms · 10 samples
93% · -7%$4.50Use in playground
H200eu-north2works2.0 GB3m 52s16 msp50 warm model time
p95 17 ms · 11 samples
81% · -19%$4.50Use in playground
H200us-central1works2.0 GB4m 10s17 msp50 warm model time
p95 18 ms · 10 samples
76% · -24%$4.50Use in playground
L40Seu-north1works1.9 GB1m 5s23 msp50 warm model time
p95 28 ms · p99 30 ms · 11 samples
57% · -43%$1.82Use in playground
RTX6000—incompatible——————
How we measure

Model time uses the p50 warm model-reported execution time when available, then falls back to the latest probe time; p95/p99 and sample count appear when there is enough probe history. Cold start excludes the first (uncached) run. VRAM is the peak GPU memory seen during the probe. Relative compares each row's model time to the highlighted baseline (fastest row by default; hover any row to re-root). The fastest chip marks only verified supported GPU-region rows. Estimated on-demand GPU price (Nebius pay-as-you-go); shown for performance/price comparison. Configured minimum GPU memory: 16 GB.

Try it out

cold·Healthcare / Life Science
Open Account
Leave GPU on “Any available GPU” to use a warm or verified backend automatically.API docs for this target
Request targetRoute/v1/inference/facebook-esm-2-650mModelfacebook-esm-2-650mVersionhf-08e4846-wrapper-20260427-timingGPUautomaticRegionautomatic

Inputs

Required fields: Protein sequence
API examples

Use the API

API docs

Snippet target: facebook-esm-2-650m version hf-08e4846-wrapper-20260427-timing using scheduler-selected GPU/region.

Client auth: Set FORGE_API_KEY to a real Forge API key before running copied curl, fetch, or SDK snippets. Browser SSO only authenticates this web session.

Open Account

Fill required inputs before copying runnable code: Protein sequence.

# Fill required inputs before copying runnable code: Protein sequence.
# Complete the required playground inputs before copying a runnable request.
Setup & .env

Install for curl

Copy setup before the request when moving this snippet into a fresh shell. The default 600 second timeout is intentional for GPU cold starts and can be overridden with FORGE_REQUEST_TIMEOUT_SECONDS.

export FORGE_API_BASE='https://YOUR_FORGE_HOST'
export FORGE_API_KEY="${FORGE_API_KEY:-replace-with-your-forge-api-key}"
export FORGE_REQUEST_TIMEOUT_SECONDS="${FORGE_REQUEST_TIMEOUT_SECONDS:-600}"

Project .env

Copy these values into a local .env file when moving the selected target into an app or SDK client.

# Forge selected target: route=/v1/inference/facebook-esm-2-650m model=facebook-esm-2-650m version=hf-08e4846-wrapper-20260427-timing
FORGE_API_BASE="https://YOUR_FORGE_HOST"
FORGE_API_ROUTE="/v1/inference/facebook-esm-2-650m"
FORGE_API_KEY="replace-with-your-forge-api-key"
FORGE_REQUEST_TIMEOUT_SECONDS="600"
MODEL_OR_FAMILY_SLUG="facebook-esm-2-650m"
FORGE_MODEL_VERSION="hf-08e4846-wrapper-20260427-timing"
Output

Run a request to see output here.

Deploy to Nebius Serverless

Run a dedicated, autoscaling endpoint in your own Nebius account. The endpoint runs under your account and billing — Forge just pre-fills the configuration for you.

Deploy in your Nebius account ↗

Opens the Nebius Console with the image pre-filled for ESM-2 650M Protein Embeddings (Forge version HF 08e4846 via Forge life-science wrapper).

Prefer to create the endpoint from the CLI, or self-manage the container image? Use the commands below.

The image is hosted on cr.eu-north1.nebius.cloud; you may need registry credentials in the Console form. The CLI below includes placeholders.

The links use Forge’s eu-north1 Nebius Container Registry mirror. If your project can’t pull that private mirror, add pull credentials or a registry secret.

nebius CLI
# Runs in YOUR Nebius account (you own + pay for the endpoint).
# platform/preset must exist in your project — list them with:
#   nebius compute platform list
export ENDPOINT_NAME="facebook-esm-2-650m-protein-embedding-private"
export AUTH_TOKEN=$(openssl rand -hex 32)
export SUBNET_ID=$(nebius vpc subnet list --format jsonpath='{.items[0].metadata.id}')
export REGISTRY_USERNAME="YOUR_REGISTRY_USERNAME"
export REGISTRY_PASSWORD="YOUR_REGISTRY_PASSWORD"

# Note: the --image above points at Forge's regional Nebius CR mirror.
#   Serverless AI can pull Container Registry images without credentials
#   only when the image is public or in the same project. For a private
#   mirror in another project, provide pull credentials or a MysteryBox
#   registry secret with REGISTRY_USERNAME and REGISTRY_PASSWORD.

nebius ai endpoint create \
  --name "$ENDPOINT_NAME" \
  --image "cr.eu-north1.nebius.cloud/e00h91c5sa606xfwpj/models/life-science-facebook-esm2-650m:20260427-timing@sha256:fd2c040ff0183a02989474910d2294a069df7685d00c1e429bd08621c715fb74" \
  --registry-username "$REGISTRY_USERNAME" \
  --registry-password "$REGISTRY_PASSWORD" \
  --container-port 8000 \
  --auth token \
  --token "$AUTH_TOKEN" \
  --subnet-id "$SUBNET_ID"

export ENDPOINT_ID=$(nebius ai endpoint get-by-name --name "$ENDPOINT_NAME" --format jsonpath='{.metadata.id}')
nebius ai endpoint get "$ENDPOINT_ID"

Need a throughput- and cost-optimized build tuned for specific Nebius GPUs? Nebius Token Factory is coming soon — contact your Nebius account team for early access.