Receipt & Invoices
Collection
13 items • Updated • 13
How to use mychen76/mistral_ocr2json_v3_chatml_GGUF with Transformers:
# Load model directly
from transformers import AutoModel
model = AutoModel.from_pretrained("mychen76/mistral_ocr2json_v3_chatml_GGUF", dtype="auto")How to use mychen76/mistral_ocr2json_v3_chatml_GGUF with llama-cpp-python:
# !pip install llama-cpp-python from llama_cpp import Llama llm = Llama.from_pretrained( repo_id="mychen76/mistral_ocr2json_v3_chatml_GGUF", filename="mistral_ocr2json_v3_chatml_GGUF-unsloth.Q4_K_M.gguf", )
llm.create_chat_completion( messages = "No input example has been defined for this model task." )
How to use mychen76/mistral_ocr2json_v3_chatml_GGUF with llama.cpp:
brew install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf mychen76/mistral_ocr2json_v3_chatml_GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf mychen76/mistral_ocr2json_v3_chatml_GGUF:Q4_K_M
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama-server -hf mychen76/mistral_ocr2json_v3_chatml_GGUF:Q4_K_M # Run inference directly in the terminal: llama-cli -hf mychen76/mistral_ocr2json_v3_chatml_GGUF:Q4_K_M
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf mychen76/mistral_ocr2json_v3_chatml_GGUF:Q4_K_M # Run inference directly in the terminal: ./llama-cli -hf mychen76/mistral_ocr2json_v3_chatml_GGUF:Q4_K_M
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf mychen76/mistral_ocr2json_v3_chatml_GGUF:Q4_K_M # Run inference directly in the terminal: ./build/bin/llama-cli -hf mychen76/mistral_ocr2json_v3_chatml_GGUF:Q4_K_M
docker model run hf.co/mychen76/mistral_ocr2json_v3_chatml_GGUF:Q4_K_M
How to use mychen76/mistral_ocr2json_v3_chatml_GGUF with Ollama:
ollama run hf.co/mychen76/mistral_ocr2json_v3_chatml_GGUF:Q4_K_M
How to use mychen76/mistral_ocr2json_v3_chatml_GGUF with Unsloth Studio:
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 mychen76/mistral_ocr2json_v3_chatml_GGUF to start chatting
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 mychen76/mistral_ocr2json_v3_chatml_GGUF to start chatting
# No setup required # Open https://huggingface.co/spaces/unsloth/studio in your browser # Search for mychen76/mistral_ocr2json_v3_chatml_GGUF to start chatting
How to use mychen76/mistral_ocr2json_v3_chatml_GGUF with Docker Model Runner:
docker model run hf.co/mychen76/mistral_ocr2json_v3_chatml_GGUF:Q4_K_M
How to use mychen76/mistral_ocr2json_v3_chatml_GGUF with Lemonade:
# Download Lemonade from https://lemonade-server.ai/ lemonade pull mychen76/mistral_ocr2json_v3_chatml_GGUF:Q4_K_M
lemonade run user.mistral_ocr2json_v3_chatml_GGUF-Q4_K_M
lemonade list
git lfs install
git clone https://huggingface.co/mychen76/mistral_ocr2json_v3_chatml-GGUF
FROM mistral_ocr2json_v3_chatml-GGUF/mistral_ocr2json_v3_chatml-Q4_K_M.gguf
TEMPLATE """{{- if .System }}
<|system|>
{{ .System }}
</s>
{{- end }}
<|user|>
{{ .Prompt }}
</s>
<|assistant|>```json
"""
PARAMETER temperature 1.0
PARAMETER num_ctx 8192
PARAMETER stop "<|system|>"
PARAMETER stop "<|user|>"
PARAMETER stop "<|assistant|>"
PARAMETER stop "</s>"
SYSTEM """
You are POS receipt data expert, parse, detect, recognize and convert following receipt OCR image result into structure receipt data object.
Don't make up value not in the Input. Output must be a well-formed JSON object.
"""
ollama create mychen76-mistral-ocr2json-v3-chatml:latest -f Modelfile
select model: mychen76-mistral-ocr2json-v3-chatml:latest
enter prompt text:
[ [[[188.0, 54.0], [453.0, 54.0], [453.0, 85.0], [188.0, 85.0]], ('The Lone Pine', 0.9998102188110352)], [[[194.0, 96.0], [449.0, 98.0], [449.0, 122.0], [194.0, 120.0]], ('43 Manchester Road', 0.9988968372344971)], [[[228.0, 127.0], [416.0, 130.0], [416.0, 154.0], [228.0, 151.0]], ('12480 Brisbane', 0.9658010601997375)], [[[267.0, 162.0], [375.0, 162.0], [375.0, 186.0], [267.0, 186.0]], ('Australia', 0.9997145533561707)], [[[234.0, 193.0], [409.0, 193.0], [409.0, 216.0], [234.0, 216.0]], ('617-3236-6207', 0.9996874332427979)], [[[46.0, 255.0], [308.0, 255.0], [308.0, 278.0], [46.0, 278.0]], ('Invoice 08000008', 0.9919923543930054)], [[[466.0, 255.0], [598.0, 255.0], [598.0, 278.0], [466.0, 278.0]], ('09/04/08', 0.9994747042655945)], [[[42.0, 283.0], [132.0, 283.0], [132.0, 311.0], [42.0, 311.0]], ('Table', 0.9969210624694824)], [[[174.0, 283.0], [214.0, 283.0], [214.0, 311.0], [174.0, 311.0]], ('25', 0.9997891783714294)], [[[514.0, 284.0], [601.0, 284.0], [601.0, 311.0], [514.0, 311.0]], ('12:45', 0.9964954257011414)], [[[67.0, 346.0], [291.0, 349.0], [291.0, 376.0], [67.0, 374.0]], ('2 Carlsberg Bottle', 0.9987921118736267)], [[[515.0, 346.0], [599.0, 346.0], [599.0, 372.0], [515.0, 372.0]], ('16.00', 0.9999278783798218)], [ [[69.0, 385.0], [395.0, 387.0], [395.0, 411.0], [69.0, 409.0]], ('3 Heineken Draft Standard.', 0.9832896590232849) ], [[[515.0, 384.0], [599.0, 384.0], [599.0, 409.0], [515.0, 409.0]], ('24.60', 0.9998160600662231)], [ [[71.0, 423.0], [391.0, 423.0], [391.0, 446.0], [71.0, 446.0]], ('1 Heineken Draft Half Liter.', 0.9641079306602478) ], [[[515.0, 421.0], [601.0, 421.0], [601.0, 450.0], [515.0, 450.0]], ('15.20', 0.9998868703842163)], [ [[69.0, 460.0], [430.0, 461.0], [430.0, 485.0], [69.0, 484.0]], ('2 Carlsberg Bucket (5 bottles).', 0.974445641040802) ], [[[515.0, 461.0], [599.0, 461.0], [599.0, 486.0], [515.0, 486.0]], ('80.00', 0.9999423027038574)], [ [[69.0, 498.0], [367.0, 500.0], [367.0, 524.0], [69.0, 522.0]], ('4 Grilled Chicken Breast.', 0.9773013591766357) ], [[[515.0, 499.0], [599.0, 499.0], [599.0, 524.0], [515.0, 524.0]], ('74.00', 0.9999669194221497)], [[[68.0, 534.0], [250.0, 537.0], [250.0, 562.0], [68.0, 560.0]], ('3 Sirloin Steak', 0.9997309446334839)], [[[515.0, 537.0], [599.0, 537.0], [599.0, 561.0], [515.0, 561.0]], ('96.00', 0.9999544024467468)], [[[67.0, 571.0], [162.0, 574.0], [161.0, 601.0], [67.0, 598.0]], ('1 Coke', 0.9997830390930176)], [[[530.0, 572.0], [602.0, 572.0], [602.0, 601.0], [530.0, 601.0]], ('3.50', 0.9999455213546753)], [[[69.0, 609.0], [219.0, 613.0], [218.0, 638.0], [68.0, 634.0]], ('5 Ice Cream', 0.9914276003837585)], [[[516.0, 611.0], [599.0, 611.0], [599.0, 637.0], [516.0, 637.0]], ('18.00', 0.9999335408210754)], [[[154.0, 664.0], [288.0, 664.0], [288.0, 688.0], [154.0, 688.0]], ('Subtotal', 0.9990750551223755)], [[[499.0, 664.0], [599.0, 664.0], [599.0, 688.0], [499.0, 688.0]], ('327.30', 0.9999768137931824)], [ [[155.0, 701.0], [397.0, 701.0], [397.0, 724.0], [155.0, 724.0]], ('Sales/Gov Tax - 5%', 0.9552016854286194) ], [[[514.0, 697.0], [601.0, 697.0], [601.0, 724.0], [514.0, 724.0]], ('16.36', 0.999823272228241)], [ [[155.0, 733.0], [419.0, 733.0], [419.0, 757.0], [155.0, 757.0]], ('Service Charge - 10%', 0.9921379089355469) ], [[[512.0, 728.0], [601.0, 731.0], [600.0, 759.0], [511.0, 757.0]], ('32.73', 0.9999620318412781)], [[[154.0, 775.0], [335.0, 775.0], [335.0, 799.0], [154.0, 799.0]], ('GRAND TOTAL', 0.9899482131004333)], [[[499.0, 778.0], [599.0, 778.0], [599.0, 802.0], [499.0, 802.0]], ('376.40', 0.9999797940254211)], [[[39.0, 831.0], [223.0, 831.0], [223.0, 859.0], [39.0, 859.0]], ('Thank you and', 0.9922393560409546)], [[[336.0, 831.0], [407.0, 831.0], [407.0, 860.0], [336.0, 860.0]], ('Cash', 0.9998616576194763)], [[[499.0, 831.0], [601.0, 831.0], [601.0, 859.0], [499.0, 859.0]], ('400.00', 0.9998554587364197)], [[[38.0, 866.0], [220.0, 862.0], [220.0, 891.0], [38.0, 895.0]], ('see you again!', 0.9798372983932495)], [[[336.0, 864.0], [438.0, 869.0], [437.0, 898.0], [335.0, 894.0]], ('Change', 0.9998979568481445)], [[[515.0, 867.0], [599.0, 867.0], [599.0, 892.0], [515.0, 892.0]], ('23.60', 0.9999337196350098)], [[[37.0, 901.0], [108.0, 901.0], [108.0, 930.0], [37.0, 930.0]], ('John', 0.9990785717964172)], [ [[73.0, 962.0], [569.0, 965.0], [569.0, 991.0], [73.0, 989.0]], ('Bring this bill back within the next 10 days', 0.9880552887916565) ], [ [[50.0, 1000.0], [591.0, 1000.0], [591.0, 1023.0], [50.0, 1023.0]], ("and get 15% discount on that day's food bill..", 0.9851154685020447) ] ]
Expect Result:
{ 'store_name': 'The Lone Pine',
'store_addr': "43 Manchester Road, Bardon, Queensland 4065Australia",
'telephone': '(07)3236-6207',
'date': '18/09/16',
'time': '11:22am',
'subtotal': '132.80',
'tax': '6.65',
'service': '50.35',
'total': '194.75',
'ignore': '',
'tips': ''
}
4-bit
Base model
unsloth/mistral-7b-instruct-v0.2-bnb-4bit