code-llama-python#
Context Length: 100000
Model Name: code-llama-python
Languages: en
Abilities: generate
Description: Code-Llama-Python is a fine-tuned version of the Code-Llama LLM, specializing in Python.
Specifications#
Model Spec 1 (pytorch, 7 Billion)#
Model Format: pytorch
Model Size (in billions): 7
Quantizations: 4-bit, 8-bit, none
Engines: vLLM, Transformers (vLLM only available for quantization none)
Model ID: TheBloke/CodeLlama-7B-Python-fp16
Model Hubs: Hugging Face, ModelScope
Execute the following command to launch the model, remember to replace ${quantization}
with your
chosen quantization method from the options listed above:
xinference launch --model-engine ${engine} --model-name code-llama-python --size-in-billions 7 --model-format pytorch --quantization ${quantization}
Model Spec 2 (pytorch, 13 Billion)#
Model Format: pytorch
Model Size (in billions): 13
Quantizations: 4-bit, 8-bit, none
Engines: vLLM, Transformers (vLLM only available for quantization none)
Model ID: TheBloke/CodeLlama-13B-Python-fp16
Model Hubs: Hugging Face, ModelScope
Execute the following command to launch the model, remember to replace ${quantization}
with your
chosen quantization method from the options listed above:
xinference launch --model-engine ${engine} --model-name code-llama-python --size-in-billions 13 --model-format pytorch --quantization ${quantization}
Model Spec 3 (pytorch, 34 Billion)#
Model Format: pytorch
Model Size (in billions): 34
Quantizations: 4-bit, 8-bit, none
Engines: vLLM, Transformers (vLLM only available for quantization none)
Model ID: TheBloke/CodeLlama-34B-Python-fp16
Model Hubs: Hugging Face
Execute the following command to launch the model, remember to replace ${quantization}
with your
chosen quantization method from the options listed above:
xinference launch --model-engine ${engine} --model-name code-llama-python --size-in-billions 34 --model-format pytorch --quantization ${quantization}
Model Spec 4 (ggufv2, 7 Billion)#
Model Format: ggufv2
Model Size (in billions): 7
Quantizations: Q2_K, Q3_K_L, Q3_K_M, Q3_K_S, Q4_0, Q4_K_M, Q4_K_S, Q5_0, Q5_K_M, Q5_K_S, Q6_K, Q8_0
Engines: llama.cpp
Model ID: TheBloke/CodeLlama-7B-Python-GGUF
Model Hubs: Hugging Face, ModelScope
Execute the following command to launch the model, remember to replace ${quantization}
with your
chosen quantization method from the options listed above:
xinference launch --model-engine ${engine} --model-name code-llama-python --size-in-billions 7 --model-format ggufv2 --quantization ${quantization}
Model Spec 5 (ggufv2, 13 Billion)#
Model Format: ggufv2
Model Size (in billions): 13
Quantizations: Q2_K, Q3_K_L, Q3_K_M, Q3_K_S, Q4_0, Q4_K_M, Q4_K_S, Q5_0, Q5_K_M, Q5_K_S, Q6_K, Q8_0
Engines: llama.cpp
Model ID: TheBloke/CodeLlama-13B-Python-GGUF
Model Hubs: Hugging Face, ModelScope
Execute the following command to launch the model, remember to replace ${quantization}
with your
chosen quantization method from the options listed above:
xinference launch --model-engine ${engine} --model-name code-llama-python --size-in-billions 13 --model-format ggufv2 --quantization ${quantization}
Model Spec 6 (ggufv2, 34 Billion)#
Model Format: ggufv2
Model Size (in billions): 34
Quantizations: Q2_K, Q3_K_L, Q3_K_M, Q3_K_S, Q4_0, Q4_K_M, Q4_K_S, Q5_0, Q5_K_M, Q5_K_S, Q6_K, Q8_0
Engines: llama.cpp
Model ID: TheBloke/CodeLlama-34B-Python-GGUF
Model Hubs: Hugging Face
Execute the following command to launch the model, remember to replace ${quantization}
with your
chosen quantization method from the options listed above:
xinference launch --model-engine ${engine} --model-name code-llama-python --size-in-billions 34 --model-format ggufv2 --quantization ${quantization}