Instructions to use anhdai312/test2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use anhdai312/test2 with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("anhdai312/test2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use anhdai312/test2 with Unsloth Studio:
Install Unsloth Studio (macOS, Linux, WSL)
curl -fsSL https://unsloth.ai/install.sh | sh # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for anhdai312/test2 to start chatting
Install Unsloth Studio (Windows)
irm https://unsloth.ai/install.ps1 | iex # Run unsloth studio unsloth studio -H 0.0.0.0 -p 8888 # Then open http://localhost:8888 in your browser # Search for anhdai312/test2 to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for anhdai312/test2 to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="anhdai312/test2", max_seq_length=2048, )
Training in progress, step 10
Browse files- README.md +3 -3
- adapter_config.json +9 -9
- adapter_model.safetensors +2 -2
- tokenizer.json +2 -2
- tokenizer_config.json +1 -41
- training_args.bin +1 -1
README.md
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---
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base_model: unsloth/
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library_name: transformers
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model_name: test2
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tags:
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- generated_from_trainer
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- trl
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- sft
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- unsloth
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licence: license
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---
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# Model Card for test2
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This model is a fine-tuned version of [unsloth/
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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---
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base_model: unsloth/qwen2.5-0.5b-instruct-unsloth-bnb-4bit
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library_name: transformers
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model_name: test2
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tags:
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- generated_from_trainer
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- unsloth
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- trl
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- sft
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licence: license
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---
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# Model Card for test2
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+
This model is a fine-tuned version of [unsloth/qwen2.5-0.5b-instruct-unsloth-bnb-4bit](https://huggingface.co/unsloth/qwen2.5-0.5b-instruct-unsloth-bnb-4bit).
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It has been trained using [TRL](https://github.com/huggingface/trl).
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## Quick start
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adapter_config.json
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"alpha_pattern": {},
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"arrow_config": null,
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"auto_mapping": {
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"base_model_class": "
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"parent_library": "transformers.models.
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"unsloth_fixed": true
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},
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"base_model_name_or_path": "unsloth/
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"bias": "none",
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"corda_config": null,
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"ensure_weight_tying": false,
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"peft_type": "LORA",
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"peft_version": "0.18.1",
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"qalora_group_size": 16,
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"r":
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"gate_proj",
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"down_proj",
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],
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"target_parameters": null,
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"task_type": "CAUSAL_LM",
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"alpha_pattern": {},
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"arrow_config": null,
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"auto_mapping": {
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"base_model_class": "Qwen2ForCausalLM",
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"parent_library": "transformers.models.qwen2.modeling_qwen2",
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"unsloth_fixed": true
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},
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"base_model_name_or_path": "unsloth/qwen2.5-0.5b-instruct-unsloth-bnb-4bit",
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"bias": "none",
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"corda_config": null,
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"ensure_weight_tying": false,
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"peft_type": "LORA",
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"peft_version": "0.18.1",
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"qalora_group_size": 16,
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"r": 8,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"up_proj",
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"q_proj",
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"o_proj",
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"down_proj",
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"v_proj",
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"gate_proj",
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"k_proj"
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],
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"target_parameters": null,
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"task_type": "CAUSAL_LM",
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adapter_model.safetensors
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tokenizer.json
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tokenizer_config.json
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"added_tokens_decoder": {
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training_args.bin
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