Instructions to use crumb/Llama-p-small with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use crumb/Llama-p-small with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="crumb/Llama-p-small", trust_remote_code=True)# Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("crumb/Llama-p-small", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use crumb/Llama-p-small with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "crumb/Llama-p-small" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "crumb/Llama-p-small", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/crumb/Llama-p-small
- SGLang
How to use crumb/Llama-p-small 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 "crumb/Llama-p-small" \ --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": "crumb/Llama-p-small", "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 "crumb/Llama-p-small" \ --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": "crumb/Llama-p-small", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use crumb/Llama-p-small with Docker Model Runner:
docker model run hf.co/crumb/Llama-p-small
Update modeling_nano.py
Browse files- modeling_nano.py +1 -1
modeling_nano.py
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@@ -94,7 +94,7 @@ class NanoAttention(nn.Module):
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elif scaling_type == "dynamic":
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self.rotary_emb = LlamaDynamicNTKScalingRotaryEmbedding(
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self.head_dim,
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-
max_position_embeddings=self.max_position_embeddings,
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scaling_factor=scaling_factor,
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base=self.config.rope_theta,
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)
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elif scaling_type == "dynamic":
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self.rotary_emb = LlamaDynamicNTKScalingRotaryEmbedding(
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self.head_dim,
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max_position_embeddings=self.config.max_position_embeddings,
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scaling_factor=scaling_factor,
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base=self.config.rope_theta,
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)
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