ludwig-ai--ludwig
wehub-resource-sync
593b94c120
pytest / Unit Tests (push) Has been cancelled
pytest / Integration (integration_tests_a) (push) Has been cancelled
pytest / Integration (integration_tests_b) (push) Has been cancelled
pytest / Integration (integration_tests_c) (push) Has been cancelled
pytest / Integration (integration_tests_d) (push) Has been cancelled
pytest / Integration (integration_tests_e) (push) Has been cancelled
pytest / Integration (integration_tests_f) (push) Has been cancelled
pytest / Integration (integration_tests_g) (push) Has been cancelled
pytest / Integration (integration_tests_h) (push) Has been cancelled
pytest / Integration (integration_tests_i) (push) Has been cancelled
pytest / Integration (integration_tests_j) (push) Has been cancelled
pytest / Distributed (distributed_a) (push) Has been cancelled
pytest / Distributed (distributed_b) (push) Has been cancelled
pytest / Distributed (distributed_c) (push) Has been cancelled
pytest / Distributed (distributed_d) (push) Has been cancelled
pytest / Distributed (distributed_e) (push) Has been cancelled
pytest / Distributed (distributed_f) (push) Has been cancelled
pytest / Minimal Install (push) Has been cancelled
pytest / Event File (push) Has been cancelled
pytest (slow) / py-slow (push) Has been cancelled
Publish JSON Schema / publish-schema (push) Has been cancelled
50 行
1.0 KiB
YAML
50 行
1.0 KiB
YAML
model_type: llm
|
|
|
|
# Qwen2-VL-7B-Instruct — swap to any HuggingFace Vision2Seq model
|
|
base_model: Qwen/Qwen2-VL-7B-Instruct
|
|
|
|
# Enable multimodal (VLM) mode.
|
|
# Ludwig loads the model with AutoModelForVision2Seq and uses AutoProcessor
|
|
# for joint tokenisation of text + image patches.
|
|
is_multimodal: true
|
|
|
|
# Trust the custom code shipped alongside Qwen2-VL on HuggingFace.
|
|
trust_remote_code: true
|
|
|
|
input_features:
|
|
- name: image_path
|
|
type: image
|
|
- name: question
|
|
type: text
|
|
|
|
output_features:
|
|
- name: answer
|
|
type: text
|
|
|
|
# LoRA adapter for parameter-efficient fine-tuning
|
|
adapter:
|
|
type: lora
|
|
r: 16
|
|
alpha: 32
|
|
target_modules: ["q_proj", "v_proj"]
|
|
|
|
trainer:
|
|
type: finetune
|
|
epochs: 3
|
|
batch_size: 4
|
|
gradient_accumulation_steps: 8
|
|
learning_rate: 2.0e-5
|
|
learning_rate_scheduler:
|
|
decay: cosine
|
|
warmup_fraction: 0.03
|
|
|
|
# 4-bit NF4 quantisation to fit the 7B model on a single 24 GB GPU
|
|
quantization:
|
|
bits: 4
|
|
quantization_type: nf4
|
|
compute_dtype: bfloat16
|
|
|
|
generation:
|
|
max_new_tokens: 256
|
|
temperature: 0.0
|