ACS Base Modelsbeta
Private beta — access is gated. Email base-models@acsresearch.org with a brief note on how you'd like to use it; we review requests individually. If it's a fit, you'll get an invite link to create an API key from the dashboard.

Using the base-model API

These are base models — raw next-token prediction, no chat template, no instruction tuning — served over an OpenAI-compatible /v1/completions endpoint.

What you get

  • Three base models — a small one for quick tests plus two larger ones (see Models). Some are kept warm; others cold-start on first use.
  • Real next-token access — arbitrary prefill/continuation, logprobs and prompt_logprobs for likelihood/surprisal and interpretability work, echo, and SSE streaming.
  • Full, honored sampling controls — temperature, top_p, top_k, min_p, penalties, and a respected seed for reproducibility.
  • A reliable, strict API — standard OpenAI-compatible /v1/completions, with strict parameter validation (a typo'd parameter fails loudly instead of silently defaulting) and clear, structured JSON errors.
  • Browser Workbench — try prompts and manage API keys without writing code.
  • Per-key budgets & usage — set token caps per key and track spend (see Account).
  • Community — a Discord with #feedback and #bug-reports, plus a one-click Feedback button in the Workbench.

Two ways in

  • Workbench — prompt the models straight from your browser. Good for getting a feel before you write any code.
  • The API (below) — for anything programmatic. Create a key from your dashboard.

Quick start

Create a key in your dashboard, then point any OpenAI-compatible client at the API:

export ACS_API_KEY="acs-bm-..."          # your key
export ACS_API_BASE="https://base-models.acsresearch.org/v1"

A first request with curl:

curl -s "$ACS_API_BASE/completions" \
  -H "Authorization: Bearer $ACS_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "llama-8b", "prompt": "The capital of France is", "max_tokens": 8}'

Or with the Python SDK (pip install openai):

import os
from openai import OpenAI

client = OpenAI(
    base_url=os.environ["ACS_API_BASE"],
    api_key=os.environ["ACS_API_KEY"],
)

resp = client.completions.create(   # completions — not chat.completions
    model="llama-8b",
    prompt="The capital of France is",
    max_tokens=16,
    logprobs=5,
)
print(resp.choices[0].text)

Worked examples

Short, copy-pasteable end-to-end snippets for each feature live under Examples — one page per topic. The curl examples assume ACS_API_KEY + ACS_API_BASE are exported (see Quick start); the Python examples use the same openai SDK client as above.

Start with logprobs if you're new — it's the smallest end-to-end example. The harder ones (with the most gotchas) are prompt_logprobs and Cold-boot recovery.