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This uses the 1b variant of Gemma 3 and a reasoning version of GSM8K dataset."},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"text","value":"🧑🍳 There’s more still in the oven like releasing models, an Unsloth version, and deeper tutorials, but hopefully this should bootstrap your projects.","raw":"🧑🍳 There’s more still in the oven like releasing models, an Unsloth version, and deeper tutorials, but hopefully this should bootstrap your projects."},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"text","value":"Here’s a link to the 1b notebook: ","raw":"Here’s a link to the 1b notebook: "},{"type":"link","href":"https://colab.research.google.com/drive/1mwCy5GQb9xJFSuwt2L_We3eKkVbx2qSt?usp=sharing","raw":"https://colab.research.google.com/drive/1mwCy5GQb9xJFSuwt2L_We3eKkVbx2qSt?usp=sharing"},{"type":"new_line","raw":"\n"}],"rawContent":"Still speed running Gemma 3 to think. Today I focused on setting up gpu poor hardware to run GRPO. \n\nThis is a plain TRL and PEFT notebook which works on mac silicone or colab T4. This uses the 1b variant of Gemma 3 and a reasoning version of GSM8K dataset.\n\n🧑🍳 There’s more still in the oven like releasing models, an Unsloth version, and deeper tutorials, but hopefully this should bootstrap your projects.\n\nHere’s a link to the 1b notebook: https://colab.research.google.com/drive/1mwCy5GQb9xJFSuwt2L_We3eKkVbx2qSt?usp=sharing\n","author":{"_id":"62d648291fa3e4e7ae3fa6e8","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/62d648291fa3e4e7ae3fa6e8/oatOwf8Xqe5eDbCSuYqCd.png","fullname":"ben burtenshaw","name":"burtenshaw","type":"user","isPro":false,"isHf":true,"isMod":false,"followerCount":1906,"isFollowing":false},"attachments":[{"type":"image","url":"https://cdn-uploads.huggingface.co/production/uploads/62d648291fa3e4e7ae3fa6e8/w7oDOan17Hk3ClIdnmPkc.png"}],"mentions":[],"reactions":[{"reaction":"👍","users":["John6666","frank0757"],"count":2},{"reaction":"🔥","users":["salym"],"count":1}],"publishedAt":"2025-03-13T15:05:23.000Z","updatedAt":"2025-03-13T15:05:23.292Z","commentators":[],"url":"/posts/burtenshaw/988620578150041","totalUniqueImpressions":352,"identifiedLanguage":{"language":"en","probability":0.8180099725723267},"numComments":0},{"slug":"224487224687488","content":[{"type":"text","value":"everybody and their dog is fine-tuning Gemma 3 today, so I thought I'd do a longer post on the tips and sharp edges I find. let's go!","raw":"everybody and their dog is fine-tuning Gemma 3 today, so I thought I'd do a longer post on the tips and sharp edges I find. let's go!"},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"text","value":"1. has to be install everything form main and nightly. this is what I'm working with to get unsloth and TRL running","raw":"1. has to be install everything form main and nightly. this is what I'm working with to get unsloth and TRL running"},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"code_fence","lang":"txt","code":"git+https://github.com/huggingface/transformers@main\ngit+https://github.com/huggingface/trl.git@main\nbitsandbytes\npeft","raw":"```txt\ngit+https://github.com/huggingface/transformers@main\ngit+https://github.com/huggingface/trl.git@main\nbitsandbytes\npeft\n```"},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"text","value":"plus this with ","raw":"plus this with "},{"type":"inline_code","code":"--no-deps","raw":"`--no-deps`"},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"code_fence","lang":"txt","code":"git+https://github.com/unslothai/unsloth-zoo.git@nightly\ngit+https://github.com/unslothai/unsloth.git@nightly","raw":"```txt\ngit+https://github.com/unslothai/unsloth-zoo.git@nightly\ngit+https://github.com/unslothai/unsloth.git@nightly\n```"},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"text","value":"2. will brown's code to turn GSM8k into a reasoning dataset is a nice toy experiment ","raw":"2. will brown's code to turn GSM8k into a reasoning dataset is a nice toy experiment "},{"type":"link","href":"https://gist.github.com/willccbb/4676755236bb08cab5f4e54a0475d6fb","raw":"https://gist.github.com/willccbb/4676755236bb08cab5f4e54a0475d6fb"},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"text","value":"3. with a learning rate of 5e-6 rewards and loss stayed flat for the first 100 or so steps.","raw":"3. with a learning rate of 5e-6 rewards and loss stayed flat for the first 100 or so steps."},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"text","value":"4. so far none of my runs have undermined the outputs after 1 epoch. therefore, I'm mainly experimenting with bigger LoRA adapters.","raw":"4. so far none of my runs have undermined the outputs after 1 epoch. therefore, I'm mainly experimenting with bigger LoRA adapters."},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"code_fence","lang":"python","code":"from trl import GRPOConfig\n\ntraining_args = GRPOConfig(\n learning_rate = 5e-6,\n adam_beta1 = 0.9,\n adam_beta2 = 0.99,\n weight_decay = 0.1,\n warmup_ratio = 0.1,\n lr_scheduler_type = \"cosine\",\n optim = \"adamw_8bit\",\n logging_steps = 1,\n per_device_train_batch_size = 2,\n gradient_accumulation_steps = 1,\n num_generations = 2,\n max_prompt_length = 256,\n max_completion_length = 1024 - 256,\n num_train_epochs = 1,\n max_steps = 250,\n save_steps = 250,\n max_grad_norm = 0.1,\n report_to = \"none\",\n)","raw":"```python\nfrom trl import GRPOConfig\n\ntraining_args = GRPOConfig(\n learning_rate = 5e-6,\n adam_beta1 = 0.9,\n adam_beta2 = 0.99,\n weight_decay = 0.1,\n warmup_ratio = 0.1,\n lr_scheduler_type = \"cosine\",\n optim = \"adamw_8bit\",\n logging_steps = 1,\n per_device_train_batch_size = 2,\n gradient_accumulation_steps = 1,\n num_generations = 2,\n max_prompt_length = 256,\n max_completion_length = 1024 - 256,\n num_train_epochs = 1,\n max_steps = 250,\n save_steps = 250,\n max_grad_norm = 0.1,\n report_to = \"none\",\n)\n```"},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"text","value":"5. vision fine-tuning isn't available in TRL's GRPOTrainer, so stick to text datasets. but no need to load the model differently in transformers or Unsloth","raw":"5. vision fine-tuning isn't available in TRL's GRPOTrainer, so stick to text datasets. but no need to load the model differently in transformers or Unsloth"},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"code_fence","lang":"python","code":"from transformers import AutoModelForImageTextToText\n\nmodel = AutoModelForImageTextToText.from_pretrained(\"google/gemma-3-4b-it)","raw":"```python\nfrom transformers import AutoModelForImageTextToText\n\nmodel = AutoModelForImageTextToText.from_pretrained(\"google/gemma-3-4b-it)\n```"},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"text","value":"if you want an introduction to GRPO, check out the reasoning course, it walks you through the algorithm, theory, and implementation in a smooth way.","raw":"if you want an introduction to GRPO, check out the reasoning course, it walks you through the algorithm, theory, and implementation in a smooth way."},{"type":"new_line","raw":"\n"},{"type":"new_line","raw":"\n"},{"type":"link","href":"https://huggingface.co/reasoning-course","raw":"https://huggingface.co/reasoning-course"}],"rawContent":"everybody and their dog is fine-tuning Gemma 3 today, so I thought I'd do a longer post on the tips and sharp edges I find. let's go!\n\n1. has to be install everything form main and nightly. this is what I'm working with to get unsloth and TRL running\n\n```txt\ngit+https://github.com/huggingface/transformers@main\ngit+https://github.com/huggingface/trl.git@main\nbitsandbytes\npeft\n```\n\nplus this with `--no-deps`\n\n```txt\ngit+https://github.com/unslothai/unsloth-zoo.git@nightly\ngit+https://github.com/unslothai/unsloth.git@nightly\n```\n\n2. will brown's code to turn GSM8k into a reasoning dataset is a nice toy experiment https://gist.github.com/willccbb/4676755236bb08cab5f4e54a0475d6fb\n\n3. with a learning rate of 5e-6 rewards and loss stayed flat for the first 100 or so steps.\n\n4. so far none of my runs have undermined the outputs after 1 epoch. therefore, I'm mainly experimenting with bigger LoRA adapters.\n\n```python\nfrom trl import GRPOConfig\n\ntraining_args = GRPOConfig(\n learning_rate = 5e-6,\n adam_beta1 = 0.9,\n adam_beta2 = 0.99,\n weight_decay = 0.1,\n warmup_ratio = 0.1,\n lr_scheduler_type = \"cosine\",\n optim = \"adamw_8bit\",\n logging_steps = 1,\n per_device_train_batch_size = 2,\n gradient_accumulation_steps = 1,\n num_generations = 2,\n max_prompt_length = 256,\n max_completion_length = 1024 - 256,\n num_train_epochs = 1,\n max_steps = 250,\n save_steps = 250,\n max_grad_norm = 0.1,\n report_to = \"none\",\n)\n```\n\n5. vision fine-tuning isn't available in TRL's GRPOTrainer, so stick to text datasets. but no need to load the model differently in transformers or Unsloth\n\n```python\nfrom transformers import AutoModelForImageTextToText\n\nmodel = AutoModelForImageTextToText.from_pretrained(\"google/gemma-3-4b-it)\n```\n\nif you want an introduction to GRPO, check out the reasoning course, it walks you through the algorithm, theory, and implementation in a smooth way.\n\nhttps://huggingface.co/reasoning-course","author":{"_id":"62d648291fa3e4e7ae3fa6e8","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/62d648291fa3e4e7ae3fa6e8/oatOwf8Xqe5eDbCSuYqCd.png","fullname":"ben burtenshaw","name":"burtenshaw","type":"user","isPro":false,"isHf":true,"isMod":false,"followerCount":1906,"isFollowing":false},"attachments":[],"mentions":[],"reactions":[{"reaction":"🤗","users":["KingNish","mshojaei77","John6666"],"count":3},{"reaction":"🔥","users":["BrigitteTousi"],"count":1}],"publishedAt":"2025-03-13T09:17:47.000Z","updatedAt":"2025-03-13T13:53:30.981Z","commentators":[{"_id":"62d648291fa3e4e7ae3fa6e8","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/62d648291fa3e4e7ae3fa6e8/oatOwf8Xqe5eDbCSuYqCd.png","fullname":"ben burtenshaw","name":"burtenshaw","type":"user","isPro":false,"isHf":true,"isMod":false,"followerCount":1906,"isFollowing":false},{"_id":"63691c3eda9b693c2730b2a2","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/63691c3eda9b693c2730b2a2/hBtKpgo3_9003MWCGkw5d.png","fullname":"Brigitte Tousignant","name":"BrigitteTousi","type":"user","isPro":false,"isHf":true,"isMod":false,"followerCount":204,"isFollowing":false}],"url":"/posts/burtenshaw/224487224687488","totalUniqueImpressions":720,"identifiedLanguage":{"language":"en","probability":0.798825204372406},"numComments":2}],"totalPosts":23,"spaces":[{"author":"burtenshaw","authorData":{"_id":"62d648291fa3e4e7ae3fa6e8","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/62d648291fa3e4e7ae3fa6e8/oatOwf8Xqe5eDbCSuYqCd.png","fullname":"ben burtenshaw","name":"burtenshaw","type":"user","isPro":false,"isHf":true,"isMod":false,"followerCount":1906},"colorFrom":"yellow","colorTo":"green","createdAt":"2025-03-06T14:47:12.000Z","emoji":"🔥","id":"burtenshaw/agent_builder","lastModified":"2025-03-06T14:56:16.000Z","likes":6,"pinned":false,"private":false,"repoType":"space","runtime":{"stage":"RUNNING","hardware":{"current":"cpu-basic","requested":"cpu-basic"},"storage":null,"gcTimeout":172800,"errorMessage":null,"replicas":{"current":1,"requested":1},"devMode":false,"domains":[{"domain":"burtenshaw-agent-builder.hf.space","stage":"READY"}],"sha":"d9c3c2064221e8c794e507a38b8c9ab65c4fc6bf"},"title":"Agent Builder","isLikedByUser":false,"ai_short_description":"Create an AI agent using Hugging Face Spaces"},{"author":"burtenshaw","authorData":{"_id":"62d648291fa3e4e7ae3fa6e8","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/62d648291fa3e4e7ae3fa6e8/oatOwf8Xqe5eDbCSuYqCd.png","fullname":"ben burtenshaw","name":"burtenshaw","type":"user","isPro":false,"isHf":true,"isMod":false,"followerCount":1906},"colorFrom":"purple","colorTo":"red","createdAt":"2025-02-27T10:19:09.000Z","emoji":"💻","id":"burtenshaw/coworking_agent","lastModified":"2025-02-27T20:02:26.000Z","likes":6,"pinned":false,"private":false,"repoType":"space","runtime":{"stage":"RUNNING","hardware":{"current":"cpu-xl","requested":"cpu-xl"},"storage":null,"gcTimeout":172800,"errorMessage":null,"replicas":{"current":1,"requested":1},"devMode":false,"domains":[{"domain":"burtenshaw-coworking-agent.hf.space","stage":"READY"}],"sha":"b92c0585d839f14303a9a676cc2f2736f848ecef"},"shortDescription":"FastRTC Voice Agent with smolagents","title":"Talk to Smolagents","isLikedByUser":false,"ai_short_description":"Find remote coworking spots via voice"},{"author":"burtenshaw","authorData":{"_id":"62d648291fa3e4e7ae3fa6e8","avatarUrl":"https://cdn-avatars.huggingface.co/v1/production/uploads/62d648291fa3e4e7ae3fa6e8/oatOwf8Xqe5eDbCSuYqCd.png","fullname":"ben burtenshaw","name":"burtenshaw","type":"user","isPro":false,"isHf":true,"isMod":false,"followerCount":1906},"colorFrom":"yellow","colorTo":"purple","createdAt":"2025-02-26T18:37:28.000Z","emoji":"📊","id":"burtenshaw/deepseek-ai-DeepSeek-R1","lastModified":"2025-02-26T18:37:28.000Z","likes":1,"pinned":false,"private":false,"repoType":"space","runtime":{"stage":"RUNTIME_ERROR","hardware":{"current":null,"requested":"cpu-basic"},"storage":null,"gcTimeout":172800,"errorMessage":"Exit code: 1. 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Still speed running Gemma 3 to think. Today I focused on setting up gpu poor hardware to run GRPO.
This is a plain TRL and PEFT notebook which works on mac silicone or colab T4. This uses the 1b variant of Gemma 3 and a reasoning version of GSM8K dataset.
🧑🍳 There’s more still in the oven like releasing models, an Unsloth version, and deeper tutorials, but hopefully this should bootstrap your projects.
