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RichardErkhov/
cognitivecomputations_-_dolphin-2.9-llama3-8b-1m-gguf

Name: cognitivecomputations_-_dolphin-2.9-llama3-8b-1m-gguf
Availability: InStock

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Quantization made by Richard Erkhov.

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dolphin-2.9-llama3-8b-1m - GGUF

Model creator: https://huggingface.co/cognitivecomputations/
Original model: https://huggingface.co/cognitivecomputations/dolphin-2.9-llama3-8b-1m/

Name	Quant method	Size
dolphin-2.9-llama3-8b-1m.Q2_K.gguf	Q2_K	2.96GB
dolphin-2.9-llama3-8b-1m.IQ3_XS.gguf	IQ3_XS	3.28GB
dolphin-2.9-llama3-8b-1m.IQ3_S.gguf	IQ3_S	3.43GB
dolphin-2.9-llama3-8b-1m.Q3_K_S.gguf	Q3_K_S	3.41GB
dolphin-2.9-llama3-8b-1m.IQ3_M.gguf	IQ3_M	3.52GB
dolphin-2.9-llama3-8b-1m.Q3_K.gguf	Q3_K	3.74GB
dolphin-2.9-llama3-8b-1m.Q3_K_M.gguf	Q3_K_M	3.74GB
dolphin-2.9-llama3-8b-1m.Q3_K_L.gguf	Q3_K_L	4.03GB
dolphin-2.9-llama3-8b-1m.IQ4_XS.gguf	IQ4_XS	4.18GB
dolphin-2.9-llama3-8b-1m.Q4_0.gguf	Q4_0	4.34GB
dolphin-2.9-llama3-8b-1m.IQ4_NL.gguf	IQ4_NL	4.38GB
dolphin-2.9-llama3-8b-1m.Q4_K_S.gguf	Q4_K_S	4.37GB
dolphin-2.9-llama3-8b-1m.Q4_K.gguf	Q4_K	4.58GB
dolphin-2.9-llama3-8b-1m.Q4_K_M.gguf	Q4_K_M	4.58GB
dolphin-2.9-llama3-8b-1m.Q4_1.gguf	Q4_1	4.78GB
dolphin-2.9-llama3-8b-1m.Q5_0.gguf	Q5_0	5.21GB
dolphin-2.9-llama3-8b-1m.Q5_K_S.gguf	Q5_K_S	5.21GB
dolphin-2.9-llama3-8b-1m.Q5_K.gguf	Q5_K	5.34GB
dolphin-2.9-llama3-8b-1m.Q5_K_M.gguf	Q5_K_M	5.34GB
dolphin-2.9-llama3-8b-1m.Q5_1.gguf	Q5_1	5.65GB
dolphin-2.9-llama3-8b-1m.Q6_K.gguf	Q6_K	6.14GB
dolphin-2.9-llama3-8b-1m.Q8_0.gguf	Q8_0	7.95GB

Original model description:

license: other base_model: meta-llama/Meta-Llama-3-8B tags:

generated_from_trainer
axolotl model-index:
name: out results: [] datasets:
cognitivecomputations/Dolphin-2.9
teknium/OpenHermes-2.5
m-a-p/CodeFeedback-Filtered-Instruction
cognitivecomputations/dolphin-coder
cognitivecomputations/samantha-data
HuggingFaceH4/ultrachat_200k
microsoft/orca-math-word-problems-200k
abacusai/SystemChat-1.1
Locutusque/function-calling-chatml
internlm/Agent-FLAN

Dolphin 2.9 Llama 3 8b 1m 🐬

Curated and trained by Eric Hartford, Lucas Atkins, and Fernando Fernandes, and Cognitive Computations

Discord

Discord: https://discord.gg/cognitivecomputations

This version of Dolphin has a 1 million token context. I have applied winglian/llama-3-1m-context-gradient-lora - created by @gradientai and @winglian and sponsored by @CrusoeCloud

A bug has been found in the Dolphin 2.9 dataset in SystemConversations that causes the model to overly talk about the "SYSTEM MESSAGE". To counter this, we recommend you add a statement in the system message directing the model not to mention the system message. An example system message is "The assistant is named Dolphin. A helpful and friendly AI assistant, Dolphin avoids discussing the system message unless directly asked about it."

My appreciation for the sponsors of Dolphin 2.9:

Crusoe Cloud - provided excellent on-demand 10xL40S node

This model is based on Llama-3-8b, and is governed by META LLAMA 3 COMMUNITY LICENSE AGREEMENT

The base model has 8k context, and the full-weight fine-tuning was with 4k sequence length.

It took 2.5 days on 8x L40S provided by Crusoe Cloud

This model was trained FFT on all parameters, using ChatML prompt template format.

example:

<|im_start|>system
You are Dolphin, a helpful AI assistant.<|im_end|>
<|im_start|>user
{prompt}<|im_end|>
<|im_start|>assistant

Dolphin-2.9 has a variety of instruction, conversational, and coding skills. It also has initial agentic abilities and supports function calling.

Dolphin is uncensored. I have filtered the dataset to remove alignment and bias. This makes the model more compliant. You are advised to implement your own alignment layer before exposing the model as a service. It will be highly compliant with any requests, even unethical ones. Please read my blog post about uncensored models. https://erichartford.com/uncensored-models You are responsible for any content you create using this model. Enjoy responsibly.

Dolphin is licensed according to Meta's Llama license. I grant permission for any use, including commercial, that falls within accordance with Meta's Llama-3 license. Dolphin was trained on data generated from GPT4, among other models.

See axolotl config

axolotl version: 0.4.0

yaml

base_model: meta-llama/Meta-Llama-3-8B
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer
tokenizer_use_fast: false


load_in_8bit: false
load_in_4bit: false
strict: false
model_config:

datasets:
  - path: /workspace/datasets/dolphin-2.9/dolphin201-sharegpt2.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/Ultrachat200kunfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/dolphin-coder-translate-sharegpt2.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/dolphin-coder-codegen-sharegpt2.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/m-a-p_Code-Feedback-sharegpt-unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/m-a-p_CodeFeedback-Filtered-Instruction-sharegpt-unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/not_samantha_norefusals.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/Orca-Math-resort-unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/agent_instruct_react_unfiltered.jsonl
    type: sharegpt  
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/toolbench_instruct_j1s1_3k_unfiltered.jsonl
    type: sharegpt  
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/toolbench_negative_unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/toolbench_react_10p_unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/toolbench_tflan_cot_30p_unfiltered.jsonl
    type: sharegpt
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/openhermes200k_unfiltered.jsonl
    type: sharegpt 
    conversation: chatml
  - path: /workspace/datasets/dolphin-2.9/SystemConversations.jsonl
    type: sharegpt
    conversation: chatml

chat_template: chatml
    

dataset_prepared_path: /workspace/datasets/dolphin-2.9/thingy
val_set_size: 0.0002
output_dir: ./out

sequence_len: 4096
sample_packing: true
pad_to_sequence_len: true

gradient_accumulation_steps: 4
micro_batch_size: 3
num_epochs: 3
logging_steps: 1
optimizer: adamw_8bit
lr_scheduler: cosine
learning_rate: 2e-5

wandb_project: dolphin-2.9-mixtral-8x22b
wandb_watch:
wandb_run_id:
wandb_log_model:

train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false

gradient_checkpointing: true
gradient_checkpointing_kwargs:
  use_reentrant: false
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true
saves_per_epoch: 4
save_total_limit: 2
save_steps:
evals_per_epoch: 4
eval_sample_packing: false
debug:
deepspeed: deepspeed_configs/zero3_bf16.json
weight_decay: 0.05
fsdp:
fsdp_config:
special_tokens:
  eos_token: "<|im_end|>"
  pad_token: "<|end_of_text|>"
tokens:
  - "<|im_start|>"
  - "<|im_end|>"

Quants

GGUF : https://huggingface.co/QuantFactory/dolphin-2.9-llama3-8b-GGUF

GGUF with imatrix: https://huggingface.co/bartowski/dolphin-2.9-llama3-8b-GGUF

Exllamav2: https://huggingface.co/bartowski/dolphin-2.9-llama3-8b-exl2

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 2e-05
train_batch_size: 3
eval_batch_size: 3
seed: 42
distributed_type: multi-GPU
num_devices: 8
gradient_accumulation_steps: 4
total_train_batch_size: 96
total_eval_batch_size: 24
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 7
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
1.146	0.0005	1	1.1064
0.6962	0.2501	555	0.6636
0.6857	0.5001	1110	0.6503
0.6592	0.7502	1665	0.6419
0.6465	1.0002	2220	0.6317
0.5295	1.2395	2775	0.6408
0.5302	1.4895	3330	0.6351
0.5188	1.7396	3885	0.6227
0.521	1.9896	4440	0.6168
0.3968	2.2289	4995	0.6646
0.3776	2.4789	5550	0.6619
0.3983	2.7290	6105	0.6602

Framework versions

Transformers 4.40.0
Pytorch 2.2.2+cu121
Datasets 2.18.0
Tokenizers 0.19.1

RichardErkhov/cognitivecomputations_-_dolphin-2.9-llama3-8b-1m-gguf