|
--- |
|
library_name: transformers |
|
license: apache-2.0 |
|
base_model: |
|
- EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2 |
|
- Qwen/Qwen2.5-14B |
|
datasets: |
|
- anthracite-org/kalo-opus-instruct-22k-no-refusal |
|
- Nopm/Opus_WritingStruct |
|
- Gryphe/Sonnet3.5-SlimOrcaDedupCleaned |
|
- Gryphe/Sonnet3.5-Charcard-Roleplay |
|
- Gryphe/ChatGPT-4o-Writing-Prompts |
|
- Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned |
|
- Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned |
|
- nothingiisreal/Reddit-Dirty-And-WritingPrompts |
|
- allura-org/Celeste-1.x-data-mixture |
|
- cognitivecomputations/dolphin-2.9.3 |
|
tags: |
|
- generated_from_trainer |
|
- llama-cpp |
|
- gguf-my-repo |
|
model-index: |
|
- name: EVA-Qwen2.5-14B-SFFT-v0.2 |
|
results: [] |
|
--- |
|
|
|
# Triangle104/EVA-Qwen2.5-14B-v0.2-Q6_K-GGUF |
|
This model was converted to GGUF format from [`EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2`](https://huggingface.co/EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. |
|
Refer to the [original model card](https://huggingface.co/EVA-UNIT-01/EVA-Qwen2.5-14B-v0.2) for more details on the model. |
|
|
|
--- |
|
Model details: |
|
- |
|
A RP/storywriting specialist model, full-parameter finetune of Qwen2.5-14B on mixture of synthetic and natural data. |
|
It uses Celeste 70B 0.1 data mixture, greatly expanding it to improve versatility, creativity and "flavor" of the resulting model. |
|
|
|
Version notes for 0.2: Now using the refined dataset from 32B 0.2. Major improvements in coherence, instruction following and long-context comprehension over 14B v0.1. |
|
|
|
Prompt format is ChatML. |
|
|
|
Recommended sampler values: |
|
|
|
Temperature: 0.8 |
|
Min-P: 0.05 |
|
Top-A: 0.3 |
|
Repetition Penalty: 1.03 |
|
|
|
Recommended SillyTavern presets (via CalamitousFelicitousness): |
|
|
|
Context |
|
Instruct and System Prompt |
|
|
|
|
|
Training data: |
|
|
|
Celeste 70B 0.1 data mixture minus Opus Instruct subset. See that model's card for details. |
|
Kalomaze's Opus_Instruct_25k dataset, filtered for refusals. |
|
A subset (1k rows) of ChatGPT-4o-WritingPrompts by Gryphe |
|
A subset (2k rows) of Sonnet3.5-Charcards-Roleplay by Gryphe |
|
Synthstruct and SynthRP datasets by Epiculous |
|
A subset from Dolphin-2.9.3, including filtered version of not_samantha and a small subset of systemchat. |
|
|
|
Training time and hardware: |
|
|
|
3 hours on 8xH100 SXM, provided by FeatherlessAI |
|
|
|
|
|
Model was created by Kearm, Auri and Cahvay. |
|
Special thanks: |
|
|
|
to Cahvay for his work on investigating and reprocessing the corrupted dataset, removing the single biggest source of data poisoning. |
|
to FeatherlessAI for generously providing 8xH100 SXM node for training of this model |
|
to Gryphe, Lemmy, Kalomaze, Nopm, Epiculous and CogninitiveComputations for the data |
|
and to Allura-org for support, feedback, beta-testing and doing quality control of EVA models. |
|
|
|
Built with Axolotl |
|
See axolotl config |
|
|
|
axolotl version: 0.4.1 |
|
|
|
base_model: Qwen/Qwen2.5-14B |
|
|
|
load_in_8bit: false |
|
load_in_4bit: false |
|
strict: false |
|
|
|
plugins: |
|
- axolotl.integrations.liger.LigerPlugin |
|
liger_rope: true |
|
liger_rms_norm: true |
|
liger_swiglu: true |
|
liger_fused_linear_cross_entropy: true |
|
|
|
# plugins: |
|
# - axolotl.integrations.spectrum.SpectrumPlugin |
|
|
|
# spectrum_top_fraction: 0.5 |
|
# # Optional if using a pre-scanned model as your base_model. Useful if using a model mirror |
|
# spectrum_model_name: Qwen/Qwen2.5-32B |
|
|
|
datasets: |
|
- path: datasets/Celeste_Filtered_utf8fix.jsonl |
|
type: sharegpt |
|
- path: datasets/deduped_not_samantha_norefusals.jsonl |
|
type: sharegpt |
|
- path: datasets/deduped_SynthRP-Gens_processed_ShareGPT_converted_cleaned.jsonl |
|
type: sharegpt |
|
- path: datasets/deduped_Synthstruct-Gens_processed_sharegpt_converted_cleaned.jsonl |
|
type: sharegpt |
|
- path: datasets/Gryphe-4o-WP-filtered-sharegpt_utf8fix.jsonl |
|
type: sharegpt |
|
- path: datasets/opus-instruct-22k-no_refusals-filtered_utf8fix.jsonl |
|
type: sharegpt |
|
- path: datasets/Sonnet3-5-charcard-names-filtered-sharegpt_utf8fix.jsonl |
|
type: sharegpt |
|
- path: datasets/SystemChat_subset_filtered_sharegpt_utf8fix.jsonl |
|
type: sharegpt |
|
|
|
chat_template: chatml |
|
shuffle_merged_datasets: true |
|
val_set_size: 0.001 |
|
output_dir: ./EVA-Qwen2.5-14B-SFFT-v0.2 |
|
|
|
sequence_len: 10240 |
|
sample_packing: true |
|
eval_sample_packing: false |
|
pad_to_sequence_len: true |
|
|
|
# adapter: qlora |
|
# lora_model_dir: |
|
# lora_r: 64 |
|
# lora_alpha: 128 |
|
# lora_dropout: 0.05 |
|
# lora_target_linear: true |
|
# peft_use_dora: true |
|
|
|
base_model: Qwen/Qwen2.5-14B |
|
|
|
load_in_8bit: false |
|
load_in_4bit: false |
|
strict: false |
|
|
|
plugins: |
|
- axolotl.integrations.liger.LigerPlugin |
|
liger_rope: true |
|
liger_rms_norm: true |
|
liger_swiglu: true |
|
liger_fused_linear_cross_entropy: true |
|
|
|
datasets: |
|
- path: datasets/Celeste_Filtered_utf8fix.jsonl |
|
type: sharegpt |
|
- path: datasets/deduped_not_samantha_norefusals.jsonl |
|
type: sharegpt |
|
- path: datasets/deduped_SynthRP-Gens_processed_ShareGPT_converted_cleaned.jsonl |
|
type: sharegpt |
|
- path: datasets/deduped_Synthstruct-Gens_processed_sharegpt_converted_cleaned.jsonl |
|
type: sharegpt |
|
- path: datasets/Gryphe-4o-WP-filtered-sharegpt_utf8fix.jsonl |
|
type: sharegpt |
|
- path: datasets/opus-instruct-22k-no_refusals-filtered_utf8fix.jsonl |
|
type: sharegpt |
|
- path: datasets/Sonnet3-5-charcard-names-filtered-sharegpt_utf8fix.jsonl |
|
type: sharegpt |
|
- path: datasets/SystemChat_subset_filtered_sharegpt_utf8fix.jsonl |
|
type: sharegpt |
|
|
|
chat_template: chatml |
|
shuffle_merged_datasets: true |
|
val_set_size: 0.005 |
|
output_dir: ./EVA-Qwen2.5-14B-SFFT-v0.2 |
|
|
|
sequence_len: 10240 |
|
sample_packing: true |
|
eval_sample_packing: false |
|
pad_to_sequence_len: true |
|
|
|
# adapter: qlora |
|
# lora_model_dir: |
|
# lora_r: 32 |
|
# lora_alpha: 16 |
|
# lora_dropout: 0.05 |
|
# lora_target_linear: true |
|
# peft_use_dora: true |
|
|
|
unfrozen_parameters: |
|
- ^lm_head.weight$ |
|
- ^model.embed_tokens.weight$ |
|
# mlp.down_proj layers |
|
- model.layers.1.mlp.down_proj |
|
- model.layers.35.mlp.down_proj |
|
- model.layers.38.mlp.down_proj |
|
- model.layers.37.mlp.down_proj |
|
- model.layers.36.mlp.down_proj |
|
- model.layers.15.mlp.down_proj |
|
- model.layers.11.mlp.down_proj |
|
- model.layers.12.mlp.down_proj |
|
- model.layers.34.mlp.down_proj |
|
- model.layers.44.mlp.down_proj |
|
- model.layers.45.mlp.down_proj |
|
- model.layers.9.mlp.down_proj |
|
- model.layers.41.mlp.down_proj |
|
- model.layers.33.mlp.down_proj |
|
- model.layers.43.mlp.down_proj |
|
- model.layers.40.mlp.down_proj |
|
- model.layers.13.mlp.down_proj |
|
- model.layers.8.mlp.down_proj |
|
- model.layers.39.mlp.down_proj |
|
- model.layers.10.mlp.down_proj |
|
- model.layers.14.mlp.down_proj |
|
- model.layers.16.mlp.down_proj |
|
- model.layers.31.mlp.down_proj |
|
- model.layers.32.mlp.down_proj |
|
# mlp.gate_proj layers |
|
- model.layers.1.mlp.gate_proj |
|
- model.layers.44.mlp.gate_proj |
|
- model.layers.46.mlp.gate_proj |
|
- model.layers.45.mlp.gate_proj |
|
- model.layers.43.mlp.gate_proj |
|
- model.layers.47.mlp.gate_proj |
|
- model.layers.42.mlp.gate_proj |
|
- model.layers.32.mlp.gate_proj |
|
- model.layers.27.mlp.gate_proj |
|
- model.layers.33.mlp.gate_proj |
|
- model.layers.28.mlp.gate_proj |
|
- model.layers.39.mlp.gate_proj |
|
- model.layers.41.mlp.gate_proj |
|
- model.layers.40.mlp.gate_proj |
|
- model.layers.30.mlp.gate_proj |
|
- model.layers.29.mlp.gate_proj |
|
- model.layers.31.mlp.gate_proj |
|
- model.layers.37.mlp.gate_proj |
|
- model.layers.26.mlp.gate_proj |
|
- model.layers.10.mlp.gate_proj |
|
- model.layers.38.mlp.gate_proj |
|
- model.layers.36.mlp.gate_proj |
|
- model.layers.12.mlp.gate_proj |
|
- model.layers.13.mlp.gate_proj |
|
# mlp.up_proj layers |
|
- model.layers.1.mlp.up_proj |
|
- model.layers.13.mlp.up_proj |
|
- model.layers.11.mlp.up_proj |
|
- model.layers.14.mlp.up_proj |
|
- model.layers.15.mlp.up_proj |
|
- model.layers.12.mlp.up_proj |
|
- model.layers.8.mlp.up_proj |
|
- model.layers.16.mlp.up_proj |
|
- model.layers.9.mlp.up_proj |
|
- model.layers.19.mlp.up_proj |
|
- model.layers.10.mlp.up_proj |
|
- model.layers.7.mlp.up_proj |
|
- model.layers.17.mlp.up_proj |
|
- model.layers.20.mlp.up_proj |
|
- model.layers.21.mlp.up_proj |
|
- model.layers.18.mlp.up_proj |
|
- model.layers.37.mlp.up_proj |
|
- model.layers.38.mlp.up_proj |
|
- model.layers.39.mlp.up_proj |
|
- model.layers.42.mlp.up_proj |
|
- model.layers.41.mlp.up_proj |
|
- model.layers.27.mlp.up_proj |
|
- model.layers.28.mlp.up_proj |
|
- model.layers.36.mlp.up_proj |
|
# self_attn.k_proj layers |
|
- model.layers.47.self_attn.k_proj |
|
- model.layers.39.self_attn.k_proj |
|
- model.layers.41.self_attn.k_proj |
|
- model.layers.37.self_attn.k_proj |
|
- model.layers.35.self_attn.k_proj |
|
- model.layers.44.self_attn.k_proj |
|
- model.layers.38.self_attn.k_proj |
|
- model.layers.14.self_attn.k_proj |
|
- model.layers.7.self_attn.k_proj |
|
- model.layers.12.self_attn.k_proj |
|
- model.layers.11.self_attn.k_proj |
|
- model.layers.32.self_attn.k_proj |
|
- model.layers.10.self_attn.k_proj |
|
- model.layers.8.self_attn.k_proj |
|
- model.layers.6.self_attn.k_proj |
|
- model.layers.9.self_attn.k_proj |
|
- model.layers.45.self_attn.k_proj |
|
- model.layers.42.self_attn.k_proj |
|
- model.layers.40.self_attn.k_proj |
|
- model.layers.5.self_attn.k_proj |
|
- model.layers.0.self_attn.k_proj |
|
- model.layers.33.self_attn.k_proj |
|
- model.layers.34.self_attn.k_proj |
|
- model.layers.13.self_attn.k_proj |
|
# self_attn.o_proj layers |
|
- model.layers.12.self_attn.o_proj |
|
- model.layers.5.self_attn.o_proj |
|
- model.layers.14.self_attn.o_proj |
|
- model.layers.16.self_attn.o_proj |
|
- model.layers.20.self_attn.o_proj |
|
- model.layers.13.self_attn.o_proj |
|
- model.layers.11.self_attn.o_proj |
|
- model.layers.4.self_attn.o_proj |
|
- model.layers.6.self_attn.o_proj |
|
- model.layers.19.self_attn.o_proj |
|
- model.layers.7.self_attn.o_proj |
|
- model.layers.18.self_attn.o_proj |
|
- model.layers.8.self_attn.o_proj |
|
- model.layers.38.self_attn.o_proj |
|
- model.layers.15.self_attn.o_proj |
|
- model.layers.17.self_attn.o_proj |
|
- model.layers.9.self_attn.o_proj |
|
- model.layers.10.self_attn.o_proj |
|
- model.layers.21.self_attn.o_proj |
|
- model.layers.28.self_attn.o_proj |
|
- model.layers.32.self_attn.o_proj |
|
- model.layers.35.self_attn.o_proj |
|
- model.layers.39.self_attn.o_proj |
|
- model.layers.3.self_attn.o_proj |
|
# self_attn.q_proj layers |
|
- model.layers.1.self_attn.q_proj |
|
- model.layers.2.self_attn.q_proj |
|
- model.layers.3.self_attn.q_proj |
|
- model.layers.44.self_attn.q_proj |
|
- model.layers.29.self_attn.q_proj |
|
- model.layers.45.self_attn.q_proj |
|
- model.layers.43.self_attn.q_proj |
|
- model.layers.32.self_attn.q_proj |
|
- model.layers.38.self_attn.q_proj |
|
- model.layers.19.self_attn.q_proj |
|
- model.layers.42.self_attn.q_proj |
|
- model.layers.34.self_attn.q_proj |
|
- model.layers.36.self_attn.q_proj |
|
- model.layers.40.self_attn.q_proj |
|
- model.layers.26.self_attn.q_proj |
|
- model.layers.20.self_attn.q_proj |
|
- model.layers.28.self_attn.q_proj |
|
- model.layers.39.self_attn.q_proj |
|
- model.layers.41.self_attn.q_proj |
|
- model.layers.33.self_attn.q_proj |
|
- model.layers.35.self_attn.q_proj |
|
- model.layers.25.self_attn.q_proj |
|
- model.layers.30.self_attn.q_proj |
|
- model.layers.27.self_attn.q_proj |
|
# self_attn.v_proj layers |
|
- model.layers.0.self_attn.v_proj |
|
- model.layers.7.self_attn.v_proj |
|
- model.layers.39.self_attn.v_proj |
|
- model.layers.31.self_attn.v_proj |
|
- model.layers.15.self_attn.v_proj |
|
- model.layers.10.self_attn.v_proj |
|
- model.layers.41.self_attn.v_proj |
|
- model.layers.32.self_attn.v_proj |
|
- model.layers.6.self_attn.v_proj |
|
- model.layers.33.self_attn.v_proj |
|
- model.layers.42.self_attn.v_proj |
|
- model.layers.29.self_attn.v_proj |
|
- model.layers.9.self_attn.v_proj |
|
- model.layers.14.self_attn.v_proj |
|
- model.layers.35.self_attn.v_proj |
|
- model.layers.38.self_attn.v_proj |
|
- model.layers.13.self_attn.v_proj |
|
- model.layers.30.self_attn.v_proj |
|
- model.layers.34.self_attn.v_proj |
|
- model.layers.5.self_attn.v_proj |
|
- model.layers.28.self_attn.v_proj |
|
- model.layers.37.self_attn.v_proj |
|
- model.layers.27.self_attn.v_proj |
|
- model.layers.11.self_attn.v_proj |
|
|
|
wandb_project: EVA-Qwen2.5-14B-SFFT-v0.2 |
|
wandb_entity: |
|
wandb_watch: |
|
wandb_name: Unit-02 |
|
wandb_log_model: |
|
|
|
gradient_accumulation_steps: 8 |
|
micro_batch_size: 2 |
|
num_epochs: 3 |
|
optimizer: paged_ademamix_8bit |
|
lr_scheduler: cosine |
|
learning_rate: 0.00005 |
|
max_grad_norm: 3 |
|
|
|
train_on_inputs: false |
|
group_by_length: false |
|
bf16: auto |
|
fp16: |
|
tf32: false |
|
|
|
gradient_checkpointing: "unsloth" |
|
# gradient_checkpointing_kwargs: |
|
# use_reentrant: true |
|
early_stopping_patience: |
|
resume_from_checkpoint: |
|
local_rank: |
|
logging_steps: 1 |
|
xformers_attention: |
|
flash_attention: true |
|
|
|
warmup_steps: 20 |
|
evals_per_epoch: 4 |
|
saves_per_epoch: 4 |
|
save_safetensors: true |
|
hub_model_id: |
|
hub_strategy: |
|
debug: |
|
deepspeed: deepspeed_configs/zero3_bf16.json |
|
weight_decay: 0.1 |
|
# fsdp: |
|
# - full_shard |
|
# - auto_wrap |
|
# fsdp_config: |
|
# fsdp_limit_all_gathers: true |
|
# fsdp_sync_module_states: false |
|
# fsdp_offload_params: true |
|
# fsdp_cpu_ram_efficient_loading: true |
|
# fsdp_auto_wrap_policy: TRANSFORMER_BASED_WRAP |
|
# fsdp_transformer_layer_cls_to_wrap: Qwen2DecoderLayer |
|
# fsdp_activation_checkpointing: true |
|
# fsdp_state_dict_type: SHARDED_STATE_DICT # Changed from FULL_STATE_DICT |
|
# fsdp_sharding_strategy: FULL_SHARD |
|
# fsdp_forward_prefetch: false # Added |
|
# fsdp_backward_prefetch: "BACKWARD_PRE" # Added |
|
# fsdp_backward_prefetch_limit: 1 # Added |
|
# fsdp_mixed_precision: BF16 # Added |
|
|
|
--- |
|
## Use with llama.cpp |
|
Install llama.cpp through brew (works on Mac and Linux) |
|
|
|
```bash |
|
brew install llama.cpp |
|
|
|
``` |
|
Invoke the llama.cpp server or the CLI. |
|
|
|
### CLI: |
|
```bash |
|
llama-cli --hf-repo Triangle104/EVA-Qwen2.5-14B-v0.2-Q6_K-GGUF --hf-file eva-qwen2.5-14b-v0.2-q6_k.gguf -p "The meaning to life and the universe is" |
|
``` |
|
|
|
### Server: |
|
```bash |
|
llama-server --hf-repo Triangle104/EVA-Qwen2.5-14B-v0.2-Q6_K-GGUF --hf-file eva-qwen2.5-14b-v0.2-q6_k.gguf -c 2048 |
|
``` |
|
|
|
Note: You can also use this checkpoint directly through the [usage steps](https://github.com/ggerganov/llama.cpp?tab=readme-ov-file#usage) listed in the Llama.cpp repo as well. |
|
|
|
Step 1: Clone llama.cpp from GitHub. |
|
``` |
|
git clone https://github.com/ggerganov/llama.cpp |
|
``` |
|
|
|
Step 2: Move into the llama.cpp folder and build it with `LLAMA_CURL=1` flag along with other hardware-specific flags (for ex: LLAMA_CUDA=1 for Nvidia GPUs on Linux). |
|
``` |
|
cd llama.cpp && LLAMA_CURL=1 make |
|
``` |
|
|
|
Step 3: Run inference through the main binary. |
|
``` |
|
./llama-cli --hf-repo Triangle104/EVA-Qwen2.5-14B-v0.2-Q6_K-GGUF --hf-file eva-qwen2.5-14b-v0.2-q6_k.gguf -p "The meaning to life and the universe is" |
|
``` |
|
or |
|
``` |
|
./llama-server --hf-repo Triangle104/EVA-Qwen2.5-14B-v0.2-Q6_K-GGUF --hf-file eva-qwen2.5-14b-v0.2-q6_k.gguf -c 2048 |
|
``` |
