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--- |
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language: |
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- en |
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library_name: transformers |
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pipeline_tag: text-generation |
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tags: |
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- cobalt |
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- cobalt-2 |
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- valiant |
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- valiant-labs |
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- qwen |
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- qwen-3 |
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- qwen-3-14b |
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- 14b |
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- math |
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- math-reasoning |
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- math-instruct |
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- reasoning |
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- problem-solving |
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- creative |
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- analytical |
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- expert |
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- rationality |
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- conversational |
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- chat |
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- instruct |
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base_model: Qwen/Qwen3-14B |
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datasets: |
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- zwhe99/DeepMath-103K |
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- sequelbox/Raiden-DeepSeek-R1 |
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license: apache-2.0 |
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--- |
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**[Support our open-source dataset and model releases!](https://huggingface.co/spaces/sequelbox/SupportOpenSource)** |
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Cobalt 2 is a math and general reasoning specialist built on Qwen 3. |
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- Finetuned on high-difficulty problems from [the math-reasoning DeepMath dataset](https://huggingface.co/datasets/zwhe99/DeepMath-103K) generated with Deepseek R1! |
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- Improved [general and creative reasoning](https://huggingface.co/datasets/sequelbox/Raiden-DeepSeek-R1) to supplement problem-solving and general chat performance. |
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- Small model sizes allow running on local desktop and mobile, plus super-fast server inference! |
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Try Esper 3, our full-stack code, architecture, and DevOps assistant: [Qwen3-4B](https://huggingface.co/ValiantLabs/Qwen3-4B-Esper3), [Qwen3-8B](https://huggingface.co/ValiantLabs/Qwen3-8B-Esper3), [Qwen3-14B](https://huggingface.co/ValiantLabs/Qwen3-14B-Esper3) |
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## Prompting Guide |
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Cobalt 2 uses the [Qwen 3](https://huggingface.co/Qwen/Qwen3-14B) prompt format. |
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Cobalt 2 is a reasoning finetune; **we recommend enable_thinking=True for all chats.** |
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Example inference script to get started: |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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model_name = "ValiantLabs/Qwen3-14B-Cobalt2" |
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# load the tokenizer and the model |
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tokenizer = AutoTokenizer.from_pretrained(model_name) |
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model = AutoModelForCausalLM.from_pretrained( |
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model_name, |
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torch_dtype="auto", |
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device_map="auto" |
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) |
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# prepare the model input |
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prompt = "Evaluate the limit using the Central Limit Theorem: \[ \lim_{n\to\infty}p^{n}\sum_{k \geqslant{n(p^{-1}-1)}}^{\infty}\binom{n+k-1}{n-1}(1-p)^{k}. \]" |
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messages = [ |
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{"role": "user", "content": prompt} |
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] |
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text = tokenizer.apply_chat_template( |
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messages, |
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tokenize=False, |
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add_generation_prompt=True, |
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enable_thinking=True # Switches between thinking and non-thinking modes. Default is True. |
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) |
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model_inputs = tokenizer([text], return_tensors="pt").to(model.device) |
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# conduct text completion |
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generated_ids = model.generate( |
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**model_inputs, |
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max_new_tokens=32768 |
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) |
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output_ids = generated_ids[0][len(model_inputs.input_ids[0]):].tolist() |
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# parsing thinking content |
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try: |
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# rindex finding 151668 (</think>) |
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index = len(output_ids) - output_ids[::-1].index(151668) |
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except ValueError: |
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index = 0 |
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thinking_content = tokenizer.decode(output_ids[:index], skip_special_tokens=True).strip("\n") |
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content = tokenizer.decode(output_ids[index:], skip_special_tokens=True).strip("\n") |
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print("thinking content:", thinking_content) |
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print("content:", content) |
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``` |
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Cobalt 2 is created by [Valiant Labs.](http://valiantlabs.ca/) |
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[Check out our HuggingFace page to see Esper 3 and all of our models!](https://huggingface.co/ValiantLabs) |
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We care about open source. For everyone to use. |
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