Instructions to use chan4lk/excel-column-mapper with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use chan4lk/excel-column-mapper with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("chan4lk/excel-column-mapper") prompt = "Write a story about Einstein" messages = [{"role": "user", "content": prompt}] prompt = tokenizer.apply_chat_template( messages, add_generation_prompt=True ) text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
- Pi new
How to use chan4lk/excel-column-mapper with Pi:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "chan4lk/excel-column-mapper"
Configure the model in Pi
# Install Pi: npm install -g @mariozechner/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "mlx-lm": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "chan4lk/excel-column-mapper" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Hermes Agent new
How to use chan4lk/excel-column-mapper with Hermes Agent:
Start the MLX server
# Install MLX LM: uv tool install mlx-lm # Start a local OpenAI-compatible server: mlx_lm.server --model "chan4lk/excel-column-mapper"
Configure Hermes
# Install Hermes: curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash hermes setup # Point Hermes at the local server: hermes config set model.provider custom hermes config set model.base_url http://127.0.0.1:8080/v1 hermes config set model.default chan4lk/excel-column-mapper
Run Hermes
hermes
- MLX LM
How to use chan4lk/excel-column-mapper with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Interactive chat REPL mlx_lm.chat --model "chan4lk/excel-column-mapper"
Run an OpenAI-compatible server
# Install MLX LM uv tool install mlx-lm # Start the server mlx_lm.server --model "chan4lk/excel-column-mapper" # Calling the OpenAI-compatible server with curl curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "chan4lk/excel-column-mapper", "messages": [ {"role": "user", "content": "Hello"} ] }'
Model Card for Model ID
Generate Synthetic Data
If you don't have your own labeled sentiment data, you can generate synthetic service desk ticket data:
https://github.com/chan4lk/langgraph-workflows
uv run generate.py
MLX Train
uv add mlx_lm
uv run mlx_lm.lora --model microsoft/Phi-3-mini-4k-instruct --train --data ./data --iters 1000
uv run mlx_lm.lora --model Qwen/Qwen3-0.6B-MLX-4bit --train --data ./data --iters 1000 --batch-size 1 --max-seq-length 1024 --num-layers 2 --fine-tune-type lora
MLX Evaluate
uv run mlx_lm.generate --model Qwen/Qwen3-0.6B-MLX-4bit --adapter-path ./adapters --max-token 2048 --prompt "Map the following column names from a provider facility spreadsheet to the standard Healthfirst schema:\n\nInput columns: ['ListInTheHfDirectory', 'LevelOfCare18', 'PrimarySpecialty', 'FridayFrom', 'EmailAddress', 'PointOfContact', 'NpiNumber', 'FridayTo', 'DseFacilityRequestType', 'LevelOfCare25', 'City', 'Language4', 'Telephone', 'LevelOfCare19', 'LevelOfCare7', 'Corporation/GroupPayToName', 'MigrationFlag', 'RowNumber']\n\nStandard schema categories and columns:\n{\n \"request_info\": [\n \"DSE Facility Request Type\",\n \"Effective Date\",\n \"Healthfirst Provider ID\"\n ],\n \"facility_basic\": [\n \"Facility Type\",\n \"Facility Name\",\n \"Medicare Number\",\n \"Medicaid Number\",\n \"NPI\",\n \"TIN\",\n \"Taxonomy\"\n ],\n \"location\": [\n \"Practice Name\",\n \"Street Address\",\n \"City\",\n \"State\",\n \"Zip Code\",\n \"County\",\n \"Phone\",\n \"Fax\"\n ],\n \"contact\": [\n \"Primary Contact Name\",\n \"Primary Contact Email\"\n ],\n \"hospital_affiliation\": [\n \"In-Network Hospital Name\"\n ],\n \"office_hours\": [\n \"Monday From\",\n \"Monday To\",\n \"Tuesday From\",\n \"Tuesday To\",\n \"Wednesday From\",\n \"Wednesday To\",\n \"Thursday From\",\n \"Thursday To\",\n \"Friday From\",\n \"Friday To\",\n \"Saturday From\",\n \"Saturday To\",\n \"Sunday From\",\n \"Sunday To\"\n ],\n \"directory_info\": [\n \"List in the HF Directory\",\n \"Language 1\",\n \"Language 2\",\n \"Language 3\",\n \"Language 4\",\n \"Language 5\",\n \"Age Range\",\n \"Handicap Access\",\n \"Primary Specialty\",\n \"Secondary Specialty\"\n ],\n \"remittance\": [\n \"Corporation / Group Pay To Name\",\n \"Remittance Street Address\",\n \"Remittance City\",\n \"Remittance State\",\n \"Remittance Zip Code\"\n ],\n \"behavioral_health\": [\n \"Level of Care 1\",\n \"Level of Care 2\",\n \"Level of Care 3\",\n \"Level of Care 4\",\n \"Level of Care 5\",\n \"Level of Care 6\",\n \"Level of Care 7\",\n \"Level of Care 8\",\n \"Level of Care 9\",\n \"Level of Care 10\",\n \"Level of Care 11\",\n \"Level of Care 12\",\n \"Level of Care 13\",\n \"Level of Care 14\",\n \"Level of Care 15\",\n \"Level of Care 16\",\n \"Level of Care 17\",\n \"Level of Care 18\",\n \"Level of Care 19\",\n \"Level of Care 20\",\n \"Level of Care 21\",\n \"Level of Care 22\",\n \"Level of Care 23\",\n \"Level of Care 24\",\n \"Level of Care 25\"\n ],\n \"termination\": [\n \"Termination Reason\"\n ]\n}\n\nProvide a JSON mapping where keys are input column names and values are the corresponding standard schema column names. Only include mappings for columns that have clear matches."
uv run mlx_lm.generate --model Qwen/Qwen3-0.6B-MLX-4bit --max-token 2048 --prompt "Map the following column names from a provider facility spreadsheet to the standard Healthfirst schema:\n\nInput columns: ['ListInTheHfDirectory', 'LevelOfCare18', 'PrimarySpecialty', 'FridayFrom', 'EmailAddress', 'PointOfContact', 'NpiNumber', 'FridayTo', 'DseFacilityRequestType', 'LevelOfCare25', 'City', 'Language4', 'Telephone', 'LevelOfCare19', 'LevelOfCare7', 'Corporation/GroupPayToName', 'MigrationFlag', 'RowNumber']\n\nStandard schema categories and columns:\n{\n \"request_info\": [\n \"DSE Facility Request Type\",\n \"Effective Date\",\n \"Healthfirst Provider ID\"\n ],\n \"facility_basic\": [\n \"Facility Type\",\n \"Facility Name\",\n \"Medicare Number\",\n \"Medicaid Number\",\n \"NPI\",\n \"TIN\",\n \"Taxonomy\"\n ],\n \"location\": [\n \"Practice Name\",\n \"Street Address\",\n \"City\",\n \"State\",\n \"Zip Code\",\n \"County\",\n \"Phone\",\n \"Fax\"\n ],\n \"contact\": [\n \"Primary Contact Name\",\n \"Primary Contact Email\"\n ],\n \"hospital_affiliation\": [\n \"In-Network Hospital Name\"\n ],\n \"office_hours\": [\n \"Monday From\",\n \"Monday To\",\n \"Tuesday From\",\n \"Tuesday To\",\n \"Wednesday From\",\n \"Wednesday To\",\n \"Thursday From\",\n \"Thursday To\",\n \"Friday From\",\n \"Friday To\",\n \"Saturday From\",\n \"Saturday To\",\n \"Sunday From\",\n \"Sunday To\"\n ],\n \"directory_info\": [\n \"List in the HF Directory\",\n \"Language 1\",\n \"Language 2\",\n \"Language 3\",\n \"Language 4\",\n \"Language 5\",\n \"Age Range\",\n \"Handicap Access\",\n \"Primary Specialty\",\n \"Secondary Specialty\"\n ],\n \"remittance\": [\n \"Corporation / Group Pay To Name\",\n \"Remittance Street Address\",\n \"Remittance City\",\n \"Remittance State\",\n \"Remittance Zip Code\"\n ],\n \"behavioral_health\": [\n \"Level of Care 1\",\n \"Level of Care 2\",\n \"Level of Care 3\",\n \"Level of Care 4\",\n \"Level of Care 5\",\n \"Level of Care 6\",\n \"Level of Care 7\",\n \"Level of Care 8\",\n \"Level of Care 9\",\n \"Level of Care 10\",\n \"Level of Care 11\",\n \"Level of Care 12\",\n \"Level of Care 13\",\n \"Level of Care 14\",\n \"Level of Care 15\",\n \"Level of Care 16\",\n \"Level of Care 17\",\n \"Level of Care 18\",\n \"Level of Care 19\",\n \"Level of Care 20\",\n \"Level of Care 21\",\n \"Level of Care 22\",\n \"Level of Care 23\",\n \"Level of Care 24\",\n \"Level of Care 25\"\n ],\n \"termination\": [\n \"Termination Reason\"\n ]\n}\n\nProvide a JSON mapping where keys are input column names and values are the corresponding standard schema column names. Only include mappings for columns that have clear matches."
## merge model
```bash
uv run mlx_lm.fuse --model Qwen/Qwen3-0.6B-MLX-4bit
```
## Upload to Huggingface
```bash
huggingface-cli upload chan4lk/excel-column-mapper /Users/chandima/repos/langgraph-workflows/fine-tuned-models/excel-column-mapper/fused_model
```
## Use LM studio
- Downloads last month
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Model size
83.9M params
Tensor type
BF16
·
U32 ·
Hardware compatibility
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4-bit