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RichardErkhov/
CultriX_-_Lama-DPOlphin-8B-gguf

Name: CultriX_-_Lama-DPOlphin-8B-gguf
Availability: InStock

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Lama-DPOlphin-8B - GGUF

Model creator: https://huggingface.co/CultriX/
Original model: https://huggingface.co/CultriX/Lama-DPOlphin-8B/

Name	Quant method	Size
Lama-DPOlphin-8B.Q2_K.gguf	Q2_K	2.96GB
Lama-DPOlphin-8B.IQ3_XS.gguf	IQ3_XS	3.28GB
Lama-DPOlphin-8B.IQ3_S.gguf	IQ3_S	3.43GB
Lama-DPOlphin-8B.Q3_K_S.gguf	Q3_K_S	3.41GB
Lama-DPOlphin-8B.IQ3_M.gguf	IQ3_M	3.52GB
Lama-DPOlphin-8B.Q3_K.gguf	Q3_K	3.74GB
Lama-DPOlphin-8B.Q3_K_M.gguf	Q3_K_M	3.74GB
Lama-DPOlphin-8B.Q3_K_L.gguf	Q3_K_L	4.03GB
Lama-DPOlphin-8B.IQ4_XS.gguf	IQ4_XS	4.18GB
Lama-DPOlphin-8B.Q4_0.gguf	Q4_0	4.34GB
Lama-DPOlphin-8B.IQ4_NL.gguf	IQ4_NL	4.38GB
Lama-DPOlphin-8B.Q4_K_S.gguf	Q4_K_S	4.37GB
Lama-DPOlphin-8B.Q4_K.gguf	Q4_K	4.58GB
Lama-DPOlphin-8B.Q4_K_M.gguf	Q4_K_M	4.58GB
Lama-DPOlphin-8B.Q4_1.gguf	Q4_1	4.78GB
Lama-DPOlphin-8B.Q5_0.gguf	Q5_0	5.21GB
Lama-DPOlphin-8B.Q5_K_S.gguf	Q5_K_S	5.21GB
Lama-DPOlphin-8B.Q5_K.gguf	Q5_K	5.34GB
Lama-DPOlphin-8B.Q5_K_M.gguf	Q5_K_M	5.34GB
Lama-DPOlphin-8B.Q5_1.gguf	Q5_1	5.65GB
Lama-DPOlphin-8B.Q6_K.gguf	Q6_K	6.14GB
Lama-DPOlphin-8B.Q8_0.gguf	Q8_0	7.95GB

Original model description:

license: apache-2.0 datasets:

mlabonne/orpo-dpo-mix-40k-flat language:
en base_model: cognitivecomputations/dolphin-2.9.4-llama3.1-8b pipeline_tag: text-generation tags:
dpo
axolotl library_name: transformers

Axolotl configuration:

yaml

base_model: cognitivecomputations/dolphin-2.9.4-llama3.1-8b
model_type: LlamaForCausalLM
tokenizer_type: AutoTokenizer
tokenizer:
  name_or_path: "https://huggingface.co/cognitivecomputations/dolphin-2.9.4-llama3.1-8b/resolve/main/tokenizer.json"


load_in_8bit: false
load_in_4bit: true
strict: false
save_safetensors: true
bnb_4bit_quant_type: "nf4"
bnb_4bit_compute_dtype: "bf16"
bnb_4bit_use_double_quant: true

rl: dpo
chat_template: chatml
datasets:
  - path: mlabonne/orpo-dpo-mix-40k-flat
    split: train
    type: chatml.intel

dataset_prepared_path: /workspace/axolotl/dataset-prepared
val_set_size: 0.0
output_dir: ./out

adapter: qlora
lora_model_dir:

sequence_len: 2048
sample_packing: false
pad_to_sequence_len: false

lora_r: 64
lora_alpha: 32
lora_dropout: 0.05
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:

wandb_project: axolotl
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:


gradient_accumulation_steps: 4  # Reduced from 8 to 4 due to large VRAM
micro_batch_size: 2  # Increased micro-batch size to 2
num_epochs: 1
optimizer: paged_adamw_8bit
lr_scheduler: cosine
learning_rate: 5e-6
train_on_inputs: false
group_by_length: false

bf16: true  # Use bf16 as it is optimal for A40 GPUs
fp16: false
tf32: true  # TF32 is supported by A40 and improves performance

gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
warmup_steps: 100
evals_per_epoch: 0
eval_table_size:
eval_table_max_new_tokens: 128
saves_per_epoch: 1
debug:
deepspeed: deepspeed_configs/zero2.json  # Enable DeepSpeed with ZeRO Stage 2
weight_decay: 0.0
special_tokens:
  pad_token: <|end_of_text|>

RichardErkhov/CultriX_-_Lama-DPOlphin-8B-gguf

Original model description:

Axolotl configuration:

RichardErkhov/
CultriX_-_Lama-DPOlphin-8B-gguf