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@ -54,7 +54,7 @@ for chunk in stream:
Run larger models by offloading to Ollama’s cloud while keeping your local workflow.
- Supported models: `deepseek-v3.1:671b-cloud`, `gpt-oss:20b-cloud`, `gpt-oss:120b-cloud`, `kimi-k2:1t-cloud`, `qwen3-coder:480b-cloud`
- Supported models: `deepseek-v3.1:671b-cloud`, `gpt-oss:20b-cloud`, `gpt-oss:120b-cloud`, `kimi-k2:1t-cloud`, `qwen3-coder:480b-cloud`, `kimi-k2-thinking` See [Ollama Models - Cloud](https://ollama.com/search?c=cloud) for more information
### Run via local Ollama
@ -70,7 +70,7 @@ ollama signin
ollama pull gpt-oss:120b-cloud
```
3) Use as usual (offloads automatically):
3) Make a request:
```python
from ollama import Client
@ -85,14 +85,14 @@ messages = [
]
for part in client.chat('gpt-oss:120b-cloud', messages=messages, stream=True):
print(part['message']['content'], end='', flush=True)
print(part.message.content, end='', flush=True)
```
### Cloud API (ollama.com)
Access cloud models directly by pointing the client at `https://ollama.com`.
1) Create an API key, then set:
1) Create an API key from [ollama.com](https://ollama.com/settings/keys) , then set:
```
export OLLAMA_API_KEY=your_api_key
@ -123,7 +123,7 @@ messages = [
]
for part in client.chat('gpt-oss:120b', messages=messages, stream=True):
print(part['message']['content'], end='', flush=True)
print(part.message.content, end='', flush=True)
```
## Custom client