Instructions to use babylm/git-2024 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use babylm/git-2024 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="babylm/git-2024", trust_remote_code=True)# Load model directly from transformers import AutoProcessor, AutoModelForImageTextToText processor = AutoProcessor.from_pretrained("babylm/git-2024", trust_remote_code=True) model = AutoModelForImageTextToText.from_pretrained("babylm/git-2024", trust_remote_code=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use babylm/git-2024 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "babylm/git-2024" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "babylm/git-2024", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/babylm/git-2024
- SGLang
How to use babylm/git-2024 with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "babylm/git-2024" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "babylm/git-2024", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "babylm/git-2024" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "babylm/git-2024", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use babylm/git-2024 with Docker Model Runner:
docker model run hf.co/babylm/git-2024
Chengxu Zhuang commited on
Commit ·
bb62585
1
Parent(s): 2cd6995
minor fix for config class
Browse files- modeling_git.py +4 -1
modeling_git.py
CHANGED
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@@ -16,9 +16,12 @@ from transformers.models.opt.modeling_opt import OPTConfig
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import transformers.models.opt.modeling_opt as hg_opt
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import transformers.models.clip.modeling_clip as modeling_clip
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from transformers.modeling_outputs import SequenceClassifierOutputWithPast
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class GitForCausalLM(modeling_git.GitForCausalLM):
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def __init__(self, *args, **kwargs):
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super().__init__(*args, **kwargs)
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@@ -219,4 +222,4 @@ class GitForSequenceClassification(modeling_git.GitPreTrainedModel):
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past_key_values=outputs.past_key_values,
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hidden_states=outputs.hidden_states,
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attentions=outputs.attentions,
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)
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import transformers.models.opt.modeling_opt as hg_opt
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import transformers.models.clip.modeling_clip as modeling_clip
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from transformers.modeling_outputs import SequenceClassifierOutputWithPast
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from .configuration_git import GitConfig
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class GitForCausalLM(modeling_git.GitForCausalLM):
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config_class = GitConfig
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def __init__(self, *args, **kwargs):
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super().__init__(*args, **kwargs)
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past_key_values=outputs.past_key_values,
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hidden_states=outputs.hidden_states,
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attentions=outputs.attentions,
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)
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