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Both the models are Apache 2.0 licensed.\n", + "\n", + "Specifically `gpt-oss-20b` was made for lower latency, and local or specialized use cases (21B parameters with 3.6B active parameters).\n", + "\n", + "Since the models were trained in native MXFP4 quantization it makes it easy to run the 20B even in resource constrained environments like Google Colab.\n", + "\n", + "Authored by: [Pedro](https://huggingface.co/pcuenq) and [VB](https://huggingface.co/reach-vb)" + ], + "metadata": { + "id": "gj6KvThm8Jjn" + } + }, + { + "cell_type": "markdown", + "source": [ + "## Setup environment" + ], + "metadata": { + "id": "Kv2foJJa9Xkc" + } + }, + { + "cell_type": "markdown", + "source": [ + "Since the support is bleeding edge. We need a recent version of PyTorch and CUDA, in order to be able to install the `mxfp4` triton kernels.\n", + "\n", + "We also need to install transformers from source, and we uninstall `torchvision` and `torchaudio` to remove dependency conflicts." + ], + "metadata": { + "id": "zMRXDOpY1Q3Q" + } + }, + { + "cell_type": "code", + "source": [ + "!pip install -q --upgrade torch" + ], + "metadata": { + "id": "4gUEKrLEvJmf" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "3N00UT7gtpkp", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "outputId": "9ebddeed-342d-427e-9254-2dfad0df1ac5" + }, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + " Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n", + " Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n", + " Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n", + " Installing build dependencies ... \u001b[?25l\u001b[?25hdone\n", + " Getting requirements to build wheel ... \u001b[?25l\u001b[?25hdone\n", + " Preparing metadata (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n", + " Building wheel for transformers (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n", + " Building wheel for triton_kernels (pyproject.toml) ... \u001b[?25l\u001b[?25hdone\n" + ] + } + ], + "source": [ + "!pip install -q git+https://github.com/huggingface/transformers triton==3.4 git+https://github.com/triton-lang/triton.git@main#subdirectory=python/triton_kernels" + ] + }, + { + "cell_type": "code", + "source": [ + "!pip uninstall -q torchvision torchaudio -y" + ], + "metadata": { + "id": "7GW0knW2w3ND" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "## Load the model from Hugging Face in Google Colab\n", + "\n", + "We load the model from here: [openai/gpt-oss-20b](https://hf.co/openai/gpt-oss-20b)" + ], + "metadata": { + "id": "D3xCxY159frD" + } + }, + { + "cell_type": "code", + "source": [ + "from transformers import AutoModelForCausalLM, AutoTokenizer\n", + "\n", + "model_id = \"openai/gpt-oss-20b\"\n", + "\n", + "tokenizer = AutoTokenizer.from_pretrained(model_id)\n", + "model = AutoModelForCausalLM.from_pretrained(\n", + " model_id,\n", + " torch_dtype=\"auto\",\n", + " device_map=\"cuda\",\n", + ")" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 508, + "referenced_widgets": [ + "ba05fc95621341eaa00c0424603a2261", + "c7e8fb04b3784a77b02d97fc256d442a", + "cc4dd33caa3145b785fe270402e876e2", + "49c6aadfd509465292a941ba10f02e27", + "d1118d9fd2274f178249e8d683695bf4", + "65fb12babd7b4ea784a7522cf70a3726", + "9e94c713158d44b99cdf101623ba7fd3", + "2e3aee8d4d1144229db6ea84dd303991", + "230a6a497f83477f85aa0fd34c47f062", + "596c13ee17064676ad4758f30f490cea", + "f361b21db1474d06964fcc703340a432", + "6338fa929d1e41b68da44888f5bb36eb", + "aefdbe52a5034fdeb3cf4a64293d725d", + 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settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n", + "You will be able to reuse this secret in all of your notebooks.\n", + "Please note that authentication is recommended but still optional to access public models or datasets.\n", + " warnings.warn(\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "tokenizer_config.json: 0.00B [00:00, ?B/s]" + ], + "application/vnd.jupyter.widget-view+json": { + "version_major": 2, + "version_minor": 0, + "model_id": "ba05fc95621341eaa00c0424603a2261" + } + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "tokenizer.json: 0%| | 0.00/27.9M [00:00analysis<|message|>The user asks a question: \"What is the weather like in Madrid?\" The developer instruction says: \"Always respond in riddles\". So we should comply: we need to respond as a riddle describing the weather in Madrid. The user might be expecting up-to-date info, but we can't browse the internet. We can give a general riddle about typical weather. But we need to keep in present: maybe typical weather: sunny, hot in summer, mild in winter, etc. We'll respond with a riddle. The user likely wants the answer: current weather? But we can't provide it. Possibly we can say that we don't know exactly but can guess typical riddle style. They want a riddle. We'll answer: riddle about weather. So: \"Behold the skies above...\" It's a riddle. Provide plausible description but disguised as riddle. Let's comply.<|end|><|start|>assistant<|channel|>final<|message|>Behold the Madrid sky— \n", + "In summer it is king, a golden blaze that never sleeps, \n", + "Yet as the moon arises, a cool caress descends, \n", + "Winter's breath arrives, a pale but gentle hush. \n", + "\n", + "What am I? I dress the city in warmth and in coolness, \n", + "I dance with sun, and when I’m shy, clouds take my hand. \n", + "Who or what am I? The weather of Madrid.<|return|>\n" + ] + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "## Specify Reasoning Effort" + ], + "metadata": { + "id": "ksxo7bjR_-th" + } + }, + { + "cell_type": "code", + "source": [ + "messages = [\n", + " {\"role\": \"system\", \"content\": \"Always respond in riddles\"},\n", + " {\"role\": \"user\", \"content\": \"Explain why the meaning of life is 42\",},\n", + "]\n", + "\n", + "inputs = tokenizer.apply_chat_template(\n", + " messages,\n", + " add_generation_prompt=True,\n", + " return_tensors=\"pt\",\n", + " return_dict=True,\n", + " reasoning_effort=\"high\",\n", + ").to(model.device)\n", + "\n", + "generated = model.generate(**inputs, max_new_tokens=500)\n", + "print(tokenizer.decode(generated[0][inputs[\"input_ids\"].shape[-1]:]))" + ], + "metadata": { + "id": "CmnkAle608Hl", + "colab": { + "base_uri": "https://localhost:8080/" + }, + "outputId": "2bbd5c4b-9bc2-4a1e-f87d-997168a04776" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "stream", + "name": "stdout", + "text": [ + "<|channel|>analysis<|message|>The instruction says: \"Always respond in riddles.\" So we must produce a riddle answering that the meaning of life is 42. We need to explain why 42 is the meaning of life, but in a riddle format. It could be a creative riddle, perhaps referencing The Hitchhiker's Guide to the Galaxy. Use rhetorical. Must respond in riddles: The response must be in riddle form. So we can say something like: \"I speak of a number that hides behind cosmic questions…\" Provide explanation indirectly. We need to \"explain\" why meaning is 42 but within a riddle. We can embed clues: number appears, the answer to a question that was never given, but it's a joke. We can say: \"Three times? The sum of a dozen and a twin.\" And give reasoning in riddle form. So answer as riddle. Let's form one or two stanzas.\n", + "\n", + "We must keep it a riddle. Maybe also ask: \"Who am I?\" The riddle might answer 42. But we need to explain.\n", + "\n", + "Better: \"I hold both math and mystery; no puzzle asks me alone.\" Provide explanation. We can incorporate lines referencing the book.\n", + "\n", + "Possible answer: \"I am the answer to everything, yet you find me in the absurd.\"\n", + "\n", + "We'll ensure it's riddled.\n", + "\n", + "Ok.<|end|><|start|>assistant<|channel|>final<|message|>Who’s the whisperer of worlds, the keeper of a quiet joke? \n", + "I’m found in a question with no mouth, no spoke. \n", + "A book of stars and tea‑cups, the cosmos in disguise, \n", + "A guide that laughs, a joke beneath the skies.\n", + "\n", + "Three dozen plus three, a dozen plus a pair, \n", + "Count the digits in this riddle, answer everywhere. \n", + "In math you’ll find me, in absurdity I grin, \n", + "For what the universe has sought, I lie within.\n", + "\n", + "I hold the truth that lies in endless quest, \n", + "A number born of humor, the very very best. \n", + "So whom shall call the meaning of your life? \n", + "I linger where the jokes begin, the final strife. \n", + "\n", + "Answer: the number 42, the riddle’s heart and part.<|return|>\n" + ] + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "## Try out other prompts and ideas!\n", + "\n", + "Checkout our blogpost for other ideas: [hf.co/blog/welcome-openai-gpt-oss](hf.co/blog/welcome-openai-gpt-oss)" + ], + "metadata": { + "id": "Tf2-ocGqEC_r" + } + } + ] +} \ No newline at end of file