Instructions to use shau1905/python_qa with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use shau1905/python_qa with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("shau1905/python_qa", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Unsloth Studio
How to use shau1905/python_qa 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 shau1905/python_qa 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 shau1905/python_qa to start chatting
Using HuggingFace Spaces for Unsloth
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for shau1905/python_qa to start chatting
Load model with FastModel
pip install unsloth from unsloth import FastModel model, tokenizer = FastModel.from_pretrained( model_name="shau1905/python_qa", max_seq_length=2048, )
Update adapter_config.json
Browse files- adapter_config.json +0 -11
adapter_config.json
CHANGED
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{
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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": "MistralForCausalLM",
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"parent_library": "transformers.models.mistral.modeling_mistral",
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},
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"base_model_name_or_path": "unsloth/phi-3-mini-4k-instruct-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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"eva_config": null,
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"exclude_modules": null,
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 32,
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"lora_bias": false,
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"lora_dropout": 0.05,
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"lora_ga_config": null,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"peft_type": "LORA",
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"peft_version": "0.19.1",
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"qalora_group_size": 16,
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"r": 16,
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"rank_pattern": {},
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"revision": null,
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],
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"target_parameters": null,
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"task_type": "CAUSAL_LM",
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"trainable_token_indices": null,
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"use_bdlora": null,
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"use_dora": false,
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"use_qalora": false,
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"use_rslora": false
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}
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{
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"alpha_pattern": {},
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"auto_mapping": {
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"base_model_class": "MistralForCausalLM",
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"parent_library": "transformers.models.mistral.modeling_mistral",
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},
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"base_model_name_or_path": "unsloth/phi-3-mini-4k-instruct-bnb-4bit",
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"bias": "none",
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 32,
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"lora_dropout": 0.05,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"peft_type": "LORA",
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"peft_version": "0.19.1",
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"r": 16,
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"rank_pattern": {},
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"revision": null,
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],
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"target_parameters": null,
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"task_type": "CAUSAL_LM",
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"use_dora": false,
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"use_rslora": false
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}
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