| --- |
| language: |
| - en |
| license: other |
| license_name: proprietary |
| license_link: LICENSE |
| tags: |
| - emotional-intelligence |
| - conversational |
| base_model: |
| - Qwen/Qwen3-32B |
| --- |
| # Hivemind-32B-Preview |
|
|
| Hivemind-32B-Preview is a 32B-parameter model fine-tuned for multi-turn, emotionally attentive conversation in human-facing enterprise contexts. It is built on Qwen3-32B with a training set focused on conversational depth, emotional subtext, and sustained engagement across complex interpersonal scenarios. |
|
|
| ## Model Details |
|
|
| - **Parameters:** 32B |
| - **Context length:** 40,960 tokens |
| - **Precision:** bfloat16 |
| - **Base model:** [Qwen3-32B](https://huggingface.co/Qwen/Qwen3-32B) |
| - **License:** Proprietary, subject to upstream Qwen license terms |
|
|
| ## Training |
|
|
| Hivemind-32B-Preview was fine-tuned for multi-turn, human-facing conversations involving ambiguity and emotional subtext. The training set was purpose-built from enterprise interaction data. |
|
|
| ## Intended Use |
|
|
| Hivemind-32B-Preview is designed for enterprise human-agent partnership contexts: customer support, coaching-style interactions, and similar conversational deployments where sustained emotional attentiveness matters. |
|
|
|
|
| ## Scope and Ongoing Work |
|
|
| Hivemind-32B-Preview is a preview release. As with any conversational model, it has scope boundaries we are actively refining: |
|
|
| - It is not intended as a source of medical, legal, financial, or safety-critical advice, and should not be deployed in those contexts or as a replacement for professional human support. |
| - Performance is strongest in standard conversational scenarios. |
|
|
| We welcome failure-case reports from researchers and deployment partners at contact@hivelabs.dev. |
|
|
| ## Usage |
|
|
| ### vLLM (recommended) |
|
|
| ```bash |
| vllm serve HiveLabsAI/hivemind-32b-preview --dtype bfloat16 |
| ``` |
|
|
| ### Transformers |
|
|
| ```python |
| from transformers import AutoModelForCausalLM, AutoTokenizer |
| |
| model_id = "HiveLabsAI/hivemind-32b-preview" |
| tokenizer = AutoTokenizer.from_pretrained(model_id) |
| model = AutoModelForCausalLM.from_pretrained( |
| model_id, |
| torch_dtype="bfloat16", |
| device_map="auto", |
| ) |
| |
| messages = [{"role": "user", "content": "Your message here"}] |
| inputs = tokenizer.apply_chat_template( |
| messages, return_tensors="pt", add_generation_prompt=True |
| ).to(model.device) |
| outputs = model.generate( |
| inputs, max_new_tokens=2048, temperature=0.6, top_p=0.95, top_k=20 |
| ) |
| print(tokenizer.decode(outputs[0][inputs.shape[-1]:], skip_special_tokens=True)) |
| ``` |
|
|
| ## About |
|
|
| Hivemind is developed by [Hive Labs](https://hivelabs.dev). For research collaboration, deployment questions, or to report failure cases, contact contact@hivelabs.dev. |
