Local LLMs

**Running DeepSeek R1 on LLM Studio**

If you’re looking to experiment with the new DeepSeek R1 model, LLM Studio makes it a breeze. Here’s a quick step‑by‑step guide:

1. **Install LLM Studio**
“`bash
pip install llm-studio
“`

2. **Download DeepSeek R1**
“`bash
llm-studio download deepseek-r1
“`

3. **Launch the Studio UI**
“`bash
llm-studio serve
“`
Open your browser at `http://localhost:8000` (or the port shown).

4. **Select the Model**
In the UI, choose “DeepSeek R1” from the model dropdown. LLM Studio will automatically pull in the required weights and tokenizer.

5. **Start Chatting**
Type a prompt, hit *Enter*, and watch DeepSeek R1 generate responses in real time.
– Use the “Advanced” tab to tweak temperature, max tokens, etc.
– The “History” panel lets you keep a conversation thread.

6. **Fine‑Tuning (Optional)**
If you want to fine‑tune on your own data, click “Fine‑Tune” → upload a CSV/JSONL file and hit *Start*. LLM Studio handles the training loop for you.

**Why LLM Studio?**
– Zero‑config GPU setup (auto‑detects CUDA).
– Built‑in inference server with low latency.
– Easy switching between models—just change the dropdown.

Give it a try and let us know how DeepSeek R1 performs for your use case!