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Sponsored by
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mlabonne / EvolCodeLlama-7b
Model's Last Updated: May 27 2025
text-generation
Introduction of EvolCodeLlama-7b
Model Details of EvolCodeLlama-7b
🦙💻 EvolCodeLlama-7b
📝 Article
This is a
codellama/CodeLlama-7b-hf
model fine-tuned using QLoRA (4-bit precision) on the
mlabonne/Evol-Instruct-Python-1k
.
🔧 Training
It was trained on an RTX 3090 in 1h 11m 44s with the following configuration file:
base_model: codellama/CodeLlama-7b-hf
base_model_config: codellama/CodeLlama-7b-hf
model_type: LlamaForCausalLM
tokenizer_type: LlamaTokenizer
is_llama_derived_model: true
hub_model_id: EvolCodeLlama-7b
load_in_8bit: false
load_in_4bit: true
strict: false
datasets:
- path: mlabonne/Evol-Instruct-Python-1k
type: alpaca
dataset_prepared_path: last_run_prepared
val_set_size: 0.02
output_dir: ./qlora-out
adapter: qlora
lora_model_dir:
sequence_len: 2048
sample_packing: true
lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_modules:
lora_target_linear: true
lora_fan_in_fan_out:
wandb_project: axolotl
wandb_entity:
wandb_watch:
wandb_run_id:
wandb_log_model:
gradient_accumulation_steps: 1
micro_batch_size: 10
num_epochs: 3
optimizer: paged_adamw_32bit
lr_scheduler: cosine
learning_rate: 0.0002
train_on_inputs: false
group_by_length: false
bf16: true
fp16: false
tf32: false
gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
warmup_steps: 100
eval_steps: 0.01
save_strategy: epoch
save_steps:
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
bos_token: "<s>"
eos_token: "</s>"
unk_token: "<unk>"
Here are the loss curves:
It is mainly designed for educational purposes, not for inference.
💻 Usage
# pip install transformers accelerate
from transformers import AutoTokenizer
import transformers
import torch
model = "mlabonne/EvolCodeLlama-7b"
prompt = "Your prompt"
tokenizer = AutoTokenizer.from_pretrained(model)
pipeline = transformers.pipeline(
"text-generation",
model=model,
torch_dtype=torch.float16,
device_map="auto",
)
sequences = pipeline(
f'{prompt}',
do_sample=True,
top_k=10,
num_return_sequences=1,
eos_token_id=tokenizer.eos_token_id,
max_length=200,
)
for seq in sequences:
print(f"Result: {seq['generated_text']}")
Runs of mlabonne EvolCodeLlama-7b on huggingface.co
43
Total runs
0
24-hour runs
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3-day runs
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7-day runs
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30-day runs
More Information About EvolCodeLlama-7b huggingface.co Model
Url of EvolCodeLlama-7b
EvolCodeLlama-7b huggingface.co Url
Provider of EvolCodeLlama-7b huggingface.co
Other API from mlabonne
Updated:May 19 2025
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