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Model: kth8/gemma-3-1b-it-IFeval
Source: Original Platform

.gitattributes

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README.md

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+---
+license: gemma
+language:
+- en
+base_model: unsloth/gemma-3-1b-it
+datasets:
+- HuggingFaceH4/ifeval-like-data
+pipeline_tag: text-generation
+library_name: transformers
+tags:
+- sft
+- trl
+- unsloth
+- google
+- gemma
+- gemma3
+- gemma3_text
+---
+![logo](https://storage.googleapis.com/gweb-developer-goog-blog-assets/images/gemma-3_2.original.png)
+A fine-tune of [unsloth/gemma-3-1b-it](https://huggingface.co/unsloth/gemma-3-1b-it) on the [HuggingFaceH4/ifeval-like-data](https://huggingface.co/datasets/HuggingFaceH4/ifeval-like-data) dataset.
+
+## Usage example
+**System prompt**
+```
+You are a helpful assistant.
+```
+**User prompt**
+```
+We want to teach our daughter the value of a clean home. Can you suggest chores that are appropriate for a child who is who 5 years old?
+```
+**Assistant response**
+```
+No Problem! Here are some great chores for a 5-year-old to do. 
+
+     • Vacuuming: Most kids love the vacuum so this is a great starter chore for a five-year-old. Make sure to go through the do’s and don’t of vacuuming and remind your child not everything gets picked up by a 
+       vacuum. 
+     • Bedroom Cleanup: Teach your child to take care of their bedrooms. Start with picking up toys, this can be made into a game by color or items. Another good way of teaching children to fine-tune their bedrooms is 
+       lining up their shoes, making their beds, and ensuring nothing is out of order. 
+     • Separate Laundry: At 5 a children can easily distinguish between colors, whites, and towels. Have your children separate the laundry to make the task of washing clothes easier and more efficient. 
+     • Folding Laundry: This is a great time to teach children how to fold laundry. At 5 they won’t be perfect but little hands can handle washcloths, hand towels, and mating socks. 
+     • Putting Away Groceries: This is a good way for children to learn everything has a place to go. With your guidance, a small task like putting away groceries will teach them later on how to put away and keep things 
+       neat. 
+     • Dusting: Grab a duster and teach your child how to carefully remove things to dust tables, handrails, or other kid-friendly dustable areas. 
+     • Set and Clean The Table: Most households with small kids have kid-friendly items for the table. Allow your child to set the table before dinner.  After dinner teach your child to remove their items and take them to 
+        the kitchen sink to be rinsed off. This chore will become a healthy habit. 
+     • Make The Bed: At five this won’t be perfect, but a child will be able to learn to set the pillow properly and adjust their bedding so it's more tidy. If they use extra blankets at night teach them to put them away or 
+       fold them at the bottom of the bed. Don’t forget to adjust the stuffed animals!
+
+```
+## Model Details
+- Base Model: `unsloth/gemma-3-1b-it`
+- Parameter Count: 999,885,952
+- Precision: torch.bfloat16
+
+## Hardware
+- GPU: NVIDIA RTX PRO 6000 Blackwell Server Edition
+- Announced: Mar 17th, 2025
+- Release Date: Mar 18th, 2025
+- Memory Type: GDDR7
+- Bandwidth: 1.79 TB/s
+- Memory Size: 96 GB
+- Memory Bus: 512 bit
+- Shading Units: 24064
+- TDP: 600W
+
+## Training Settings
+### PEFT
+- Rank: 32
+- LoRA alpha: 64
+- Modules: q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj
+- Gradient checkpointing: unsloth
+
+### SFT
+- Epoch: 2
+- Batch size: 16
+- Gradient Accumulation steps: 1
+- Warmup ratio: 0.05
+- Learning rate: 0.0004
+- Optimizer: adamw_torch_fused
+- Learning rate scheduler: cosine
+
+## Training stats
+- Date: 2026-03-24T11:16:12.098497
+- Peak VRAM usage: 34.73 GB
+- Global step: 1850
+- Training runtime (seconds): 958.4314
+- Average training loss: 1.6259772120295344
+- Final validation loss: 1.7383391857147217
+
+## Framework versions
+- Unsloth: 2026.3.10
+- TRL: 0.22.2
+- Transformers: 4.56.2
+- Pytorch: 2.10.0+cu128
+- Datasets: 4.8.4
+- Tokenizers: 0.22.2
+
+## License
+This model is released under the Gemma license. See the [Gemma Terms of Use](https://ai.google.dev/gemma/terms) and [Prohibited Use Policy](https://policies.google.com/terms/generative-ai/use-policy) regarding the use of Gemma-generated content.

added_tokens.json

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+{
+  "<image_soft_token>": 262144
+}

chat_template.jinja

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+{{ bos_token }}
+{%- if messages[0]['role'] == 'system' -%}
+    {%- if messages[0]['content'] is string -%}
+        {%- set first_user_prefix = messages[0]['content'] + '
+
+' -%}
+    {%- else -%}
+        {%- set first_user_prefix = messages[0]['content'][0]['text'] + '
+
+' -%}
+    {%- endif -%}
+    {%- set loop_messages = messages[1:] -%}
+{%- else -%}
+    {%- set first_user_prefix = "" -%}
+    {%- set loop_messages = messages -%}
+{%- endif -%}
+{%- for message in loop_messages -%}
+    {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}
+        {{ raise_exception("Conversation roles must alternate user/assistant/user/assistant/...") }}
+    {%- endif -%}
+    {%- if (message['role'] == 'assistant') -%}
+        {%- set role = "model" -%}
+    {%- else -%}
+        {%- set role = message['role'] -%}
+    {%- endif -%}
+    {{ '<start_of_turn>' + role + '
+' + (first_user_prefix if loop.first else "") }}
+    {%- if message['content'] is string -%}
+        {{ message['content'] | trim }}
+    {%- elif message['content'] is iterable -%}
+        {%- for item in message['content'] -%}
+            {%- if item['type'] == 'image' -%}
+                {{ '<start_of_image>' }}
+            {%- elif item['type'] == 'text' -%}
+                {{ item['text'] | trim }}
+            {%- endif -%}
+        {%- endfor -%}
+    {%- else -%}
+        {{ raise_exception("Invalid content type") }}
+    {%- endif -%}
+    {{ '<end_of_turn>
+' }}
+{%- endfor -%}
+{%- if add_generation_prompt -%}
+    {{'<start_of_turn>model
+'}}
+{%- endif -%}

config.json

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+{
+  "_sliding_window_pattern": 6,
+  "architectures": [
+    "Gemma3ForCausalLM"
+  ],
+  "attention_bias": false,
+  "attention_dropout": 0.0,
+  "attn_logit_softcapping": null,
+  "bos_token_id": 2,
+  "cache_implementation": "hybrid",
+  "dtype": "bfloat16",
+  "eos_token_id": 106,
+  "final_logit_softcapping": null,
+  "head_dim": 256,
+  "hidden_activation": "gelu_pytorch_tanh",
+  "hidden_size": 1152,
+  "initializer_range": 0.02,
+  "intermediate_size": 6912,
+  "layer_types": [
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "sliding_attention",
+    "full_attention",
+    "sliding_attention",
+    "sliding_attention"
+  ],
+  "max_position_embeddings": 32768,
+  "model_type": "gemma3_text",
+  "num_attention_heads": 4,
+  "num_hidden_layers": 26,
+  "num_key_value_heads": 1,
+  "pad_token_id": 0,
+  "query_pre_attn_scalar": 256,
+  "rms_norm_eps": 1e-06,
+  "rope_local_base_freq": 10000,
+  "rope_scaling": null,
+  "rope_theta": 1000000,
+  "sliding_window": 512,
+  "transformers_version": "4.56.2",
+  "unsloth_fixed": true,
+  "use_cache": true,
+  "vocab_size": 262144
+}

generation_config.json

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+{
+  "bos_token_id": 2,
+  "cache_implementation": "hybrid",
+  "do_sample": true,
+  "eos_token_id": [
+    1,
+    106
+  ],
+  "max_length": 32768,
+  "pad_token_id": 0,
+  "top_k": 64,
+  "top_p": 0.95,
+  "transformers_version": "4.56.2"
+}

model.safetensors

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+size 1999811208

special_tokens_map.json

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+{
+  "boi_token": "<start_of_image>",
+  "bos_token": {
+    "content": "<bos>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eoi_token": "<end_of_image>",
+  "eos_token": {
+    "content": "<end_of_turn>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "image_token": "<image_soft_token>",
+  "pad_token": {
+    "content": "<pad>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer.json

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+size 33384568

tokenizer.model

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