This is a series of models designed to replicate the prose quality of the Claude 3 models, specifically Sonnet and Opus.
This model is fine-tuned on top of mistralai/Mistral-Large-Instruct-2407.
Prompting
A typical input would look like this:
<s>[INST] SYSTEM MESSAGE\nUSER MESSAGE[/INST] ASSISTANT MESSAGE</s>[INST] USER MESSAGE[/INST]
SillyTavern templates
Below are Instruct and Context templates for use within SillyTavern.
default SillyTavern template works fine
default SillyTavern template works fine
Axolotl config
base_model: mistralai/Mistral-Large-Instruct-2407
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer
plugins:
- axolotl.integrations.liger.LigerPlugin
liger_rope: true
liger_rms_norm: true
liger_swiglu: true
liger_fused_linear_cross_entropy: true
load_in_8bit: false
load_in_4bit: false
strict: false
datasets:
- path: anthracite-org/c2_logs_16k_mistral-large_v1.2
type: sharegpt
conversation: mistral
- path: anthracite-org/kalo-opus-instruct-22k-no-refusal
type: sharegpt
conversation: mistral
- path: lodrick-the-lafted/kalo-opus-instruct-3k-filtered
type: sharegpt
conversation: mistral
- path: anthracite-org/nopm_claude_writing_fixed
type: sharegpt
conversation: mistral
- path: anthracite-org/kalo_opus_misc_240827
type: sharegpt
conversation: mistral
- path: anthracite-org/kalo_misc_part2
type: sharegpt
conversation: mistral
#chat_template: chatml
shuffle_merged_datasets: true
#default_system_message: "You are an assistant that responds to the user."
dataset_prepared_path: ./data/magnum-123b-data
val_set_size: 0.0
output_dir: ./data/123b-fft-out
sequence_len: 16384
sample_packing: true
pad_to_sequence_len: true
adapter:
lora_model_dir:
lora_r:
lora_alpha:
lora_dropout:
lora_target_linear:
lora_fan_in_fan_out:
wandb_project: 123b-magnum-fft
wandb_entity:
wandb_watch:
wandb_name: alter-attempt-04
wandb_log_model:
gradient_accumulation_steps: 4
micro_batch_size: 1
num_epochs: 2
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.0000015
train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false
gradient_checkpointing: unsloth
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
warmup_steps: 40
evals_per_epoch:
eval_table_size:
eval_max_new_tokens:
saves_per_epoch: 2
debug:
deepspeed: deepspeed_configs/zero3_bf16.json
weight_decay: 0.01
fsdp:
fsdp_config:
special_tokens:
Credits
We'd like to thank Eric Hartford for sponsoring the compute for this train. We would also like to thank all members of Anthracite who made this finetune possible.
Datasets
- anthracite-org/c2_logs_16k_mistral-large_v1.2
- anthracite-org/kalo-opus-instruct-22k-no-refusal
- lodrick-the-lafted/kalo-opus-instruct-3k-filtered
- anthracite-org/nopm_claude_writing_fixed
- anthracite-org/kalo_opus_misc_240827
- anthracite-org/kalo_misc_part2
Training
We used 8x mi300x GPUs graciously provided by Eric Hartford for the full-parameter fine-tuning of the model.
Safety
...