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Model: huihui-ai/MicroThinker-3B-Preview Source: Original Platform
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README.md
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README.md
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---
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license: apache-2.0
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datasets:
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- huihui-ai/FineQwQ-142k
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base_model:
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- huihui-ai/Llama-3.2-3B-Instruct-abliterated
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tags:
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- llama3.2
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- abliterated
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- uncensored
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library_name: transformers
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pipeline_tag: text-generation
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language:
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- en
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---
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# MicroThinker-3B-Preview
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MicroThinker-3B-Preview, a new model fine-tuned from the [huihui-ai/Llama-3.2-3B-Instruct-abliterated](https://huggingface.co/huihui-ai/Llama-3.2-3B-Instruct-abliterated) model, focused on advancing AI reasoning capabilities.
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## Use with ollama
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You can use [huihui_ai/microthinker](https://ollama.com/huihui_ai/microthinker) directly
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```
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ollama run huihui_ai/microthinker:3b
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```
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## Training Details
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This is just a test, but the performance is quite good.
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Now, I'll introduce the test environment.
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The model was trained using 1 RTX 4090 GPU(24GB) .
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The fine-tuning process used 142k from the FineQwQ-142k dataset, max_length(tokens) 21710, quant_bits 4.
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The [SFT (Supervised Fine-Tuning)](https://github.com/modelscope/ms-swift) process is divided into several steps, and no code needs to be written.
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1. Create the environment.
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```
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conda create -yn ms-swift python=3.11
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conda activate ms-swift
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git clone https://github.com/modelscope/ms-swift.git
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cd ms-swift
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pip install -e .
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cd ..
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```
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2. Download the model and dataset.
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```
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huggingface-cli download huihui-ai/Llama-3.2-3B-Instruct-abliterated --local-dir ./huihui-ai/Llama-3.2-3B-Instruct-abliterated
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huggingface-cli download --repo-type dataset huihui-ai/FineQwQ-142k --local-dir ./data/FineQwQ-142k
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```
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3. Used only the huihui-ai/FineQwQ-142k, Trained for 1 epoch:
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```
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swift sft --model huihui-ai/Llama-3.2-3B-Instruct-abliterated --model_type llama3_2 --train_type lora --dataset "data/FineQwQ-142k/FineQwQ-142k.jsonl" --num_train_epochs 1 --per_device_train_batch_size 1 --per_device_eval_batch_size 1 --max_length 21710 --quant_bits 4 --bnb_4bit_compute_dtype bfloat16 --bnb_4bit_quant_storage bfloat16 --lora_rank 8 --lora_alpha 32 --gradient_checkpointing true --weight_decay 0.1 --learning_rate 1e-4 --gradient_accumulation_steps 16 --eval_steps 100 --save_steps 100 --logging_steps 20 --system "You are a helpful assistant. You should think step-by-step." --output_dir output/MicroThinker-3B-Preview/lora/sft --model_author "huihui-ai" --model_name "MicroThinker-3B-Preview"
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```
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4. Save the final fine-tuned model. After you're done, input `exit` to exit.
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Replace the directories below with specific ones.
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```
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swift infer --model huihui-ai/Llama-3.2-3B-Instruct-abliterated --adapters output/Llama-3.2-3B-Instruct-abliterated/lora/sft/v0-20250106-193759/checkpoint-8786 --stream true --merge_lora true
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```
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This should create a new model directory: `checkpoint-8786-merged`, Rename the directory to `MicroThinker-3B-Preview`, Copy or move this directory to the `huihui` directory.
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5. Perform inference on the final fine-tuned model.
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```
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swift infer --model huihui/MicroThinker-3B-Preview --stream true --infer_backend pt --max_new_tokens 8192
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```
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6. Test examples.
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```
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How many 'r' characters are there in the word "strawberry"?
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```
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config.json
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"head_dim": 128,
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"hidden_act": "silu",
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"hidden_size": 3072,
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"initializer_range": 0.02,
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"intermediate_size": 8192,
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"max_position_embeddings": 131072,
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"mlp_bias": false,
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"model_type": "llama",
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"num_attention_heads": 24,
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"num_hidden_layers": 28,
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"num_key_value_heads": 8,
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"pretraining_tp": 1,
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"rms_norm_eps": 1e-05,
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"rope_scaling": {
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"factor": 32.0,
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"high_freq_factor": 4.0,
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"low_freq_factor": 1.0,
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"original_max_position_embeddings": 8192,
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"rope_type": "llama3"
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"rope_theta": 500000.0,
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"tie_word_embeddings": true,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.45.0.dev0",
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"use_cache": true,
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"vocab_size": 128256
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}
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23
special_tokens_map.json
Normal file
23
special_tokens_map.json
Normal file
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||||
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||||
3
tokenizer.json
Normal file
3
tokenizer.json
Normal file
@@ -0,0 +1,3 @@
|
||||
version https://git-lfs.github.com/spec/v1
|
||||
oid sha256:65ff5472d095ccd9332d9e723153d7bc7226cb6be9c1bffda738b5ba2e71bf26
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size 17210084
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2068
tokenizer_config.json
Normal file
2068
tokenizer_config.json
Normal file
File diff suppressed because it is too large
Load Diff
Reference in New Issue
Block a user