river-client
Python client for the River ML training API — sampling, LoRA fine-tuning, and reinforcement learning against River-hosted models.
Installation
pip install river-client
Requires Python 3.12+.
Quick start
import river_client as river
client = river.Client(api_key="your-key", endpoint="api.river.ai")
# Stateless sampling from a base model
samples = client.sample(
"What is 2+2?",
base_model="Qwen/Qwen3.6-35B-A3B-FP8",
max_tokens=50,
)
print(samples[0].text)
# Training with a session
with client.session() as session:
model = session.create_model(
base_model="Qwen/Qwen3.6-35B-A3B-FP8",
lora=river.LoraConfig(rank=16),
)
# Forward + backward, then an optimizer step
result = model.forward_backward(data, loss_fn="cross_entropy")
model.optim_step(lr=1e-4)
# Sample from the current weights
sample_groups = model.sample("Continue:", max_tokens=100)
License
Apache-2.0. See LICENSE.
1 maintainer
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