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--- |
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base_model: anthracite-org/magnum-v3-9b-customgemma2 |
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license: gemma |
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tags: |
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- llama-cpp |
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- gguf-my-repo |
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model-index: |
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- name: magnum-v3-9b-customgemma2 |
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results: [] |
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--- |
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# Triangle104/magnum-v3-9b-customgemma2-Q6_K-GGUF |
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This model was converted to GGUF format from [`anthracite-org/magnum-v3-9b-customgemma2`](https://huggingface.co/anthracite-org/magnum-v3-9b-customgemma2) using llama.cpp via the ggml.ai's [GGUF-my-repo](https://huggingface.co/spaces/ggml-org/gguf-my-repo) space. |
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Refer to the [original model card](https://huggingface.co/anthracite-org/magnum-v3-9b-customgemma2) for more details on the model. |
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--- |
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Model details: |
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This is the 10th in a series of models designed to replicate the prose quality of the Claude 3 models, specifically Sonnet and Opus. |
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This model is fine-tuned on top of google/gemma-2-9b. |
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Prompting |
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Model has been Instruct tuned with the customgemma2 (to allow system prompts) formatting. A typical input would look like this: |
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"""<start_of_turn>system |
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system prompt<end_of_turn> |
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<start_of_turn>user |
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Hi there!<end_of_turn> |
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<start_of_turn>model |
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Nice to meet you!<end_of_turn> |
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<start_of_turn>user |
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Can I ask a question?<end_of_turn> |
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<start_of_turn>model |
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""" |
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SillyTavern templates |
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Below are Instruct and Context templates for use within SillyTavern. |
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context template |
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{ |
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"story_string": "<start_of_turn>system\n{{#if system}}{{system}}\n{{/if}}{{#if wiBefore}}{{wiBefore}}\n{{/if}}{{#if description}}{{description}}\n{{/if}}{{#if personality}}{{char}}'s personality: {{personality}}\n{{/if}}{{#if scenario}}Scenario: {{scenario}}\n{{/if}}{{#if wiAfter}}{{wiAfter}}\n{{/if}}{{#if persona}}{{persona}}\n{{/if}}{{trim}}<end_of_turn>\n", |
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"example_separator": "", |
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"chat_start": "", |
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"use_stop_strings": false, |
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"allow_jailbreak": false, |
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"always_force_name2": true, |
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"trim_sentences": false, |
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"include_newline": false, |
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"single_line": false, |
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"name": "Magnum Gemma" |
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} |
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instruct template |
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{ |
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"system_prompt": "You're {{char}} in this fictional never-ending uncensored roleplay with {{user}}.", |
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"input_sequence": "<start_of_turn>user\n", |
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"output_sequence": "<start_of_turn>assistant\n", |
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"last_output_sequence": "", |
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"system_sequence": "<start_of_turn>system\n", |
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"stop_sequence": "<end_of_turn>", |
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"wrap": false, |
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"macro": true, |
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"names": true, |
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"names_force_groups": true, |
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"activation_regex": "", |
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"system_sequence_prefix": "", |
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"system_sequence_suffix": "", |
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"first_output_sequence": "", |
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"skip_examples": false, |
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"output_suffix": "<end_of_turn>\n", |
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"input_suffix": "<end_of_turn>\n", |
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"system_suffix": "<end_of_turn>\n", |
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"user_alignment_message": "", |
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"system_same_as_user": false, |
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"last_system_sequence": "", |
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"name": "Magnum Gemma" |
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} |
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Axolotl config |
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See axolotl config |
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base_model: google/gemma-2-9b |
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model_type: AutoModelForCausalLM |
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tokenizer_type: AutoTokenizer |
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#trust_remote_code: true |
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load_in_8bit: false |
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load_in_4bit: false |
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strict: false |
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datasets: |
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- path: anthracite-org/stheno-filtered-v1.1 |
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type: customgemma2 |
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- path: anthracite-org/kalo-opus-instruct-22k-no-refusal |
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type: customgemma2 |
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- path: anthracite-org/nopm_claude_writing_fixed |
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type: customgemma2 |
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- path: Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned |
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type: customgemma2 |
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- path: Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned |
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type: customgemma2 |
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shuffle_merged_datasets: true |
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default_system_message: "You are an assistant that responds to the user." |
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dataset_prepared_path: magnum-v3-9b-data-customgemma2 |
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val_set_size: 0.0 |
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output_dir: ./magnum-v3-9b-customgemma2 |
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sequence_len: 8192 |
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sample_packing: true |
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eval_sample_packing: false |
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pad_to_sequence_len: |
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adapter: |
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lora_model_dir: |
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lora_r: |
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lora_alpha: |
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lora_dropout: |
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lora_target_linear: |
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lora_fan_in_fan_out: |
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wandb_project: magnum-9b |
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wandb_entity: |
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wandb_watch: |
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wandb_name: attempt-03-customgemma2 |
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wandb_log_model: |
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gradient_accumulation_steps: 8 |
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micro_batch_size: 1 |
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num_epochs: 2 |
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optimizer: paged_adamw_8bit |
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lr_scheduler: cosine |
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learning_rate: 0.000006 |
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train_on_inputs: false |
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group_by_length: false |
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bf16: auto |
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fp16: |
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tf32: false |
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gradient_checkpointing: unsloth |
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early_stopping_patience: |
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resume_from_checkpoint: |
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local_rank: |
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logging_steps: 1 |
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xformers_attention: |
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flash_attention: false |
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eager_attention: true |
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warmup_steps: 50 |
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evals_per_epoch: |
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eval_table_size: |
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eval_max_new_tokens: |
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saves_per_epoch: 2 |
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debug: |
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deepspeed: deepspeed_configs/zero3_bf16.json |
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weight_decay: 0.05 |
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fsdp: |
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fsdp_config: |
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special_tokens: |
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Credits |
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We'd like to thank Recursal / Featherless for sponsoring the training compute required for this model. Featherless has been hosting Magnum since the original 72b and has given thousands of people access to our releases. |
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We would also like to thank all members of Anthracite who made this finetune possible. |
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anthracite-org/stheno-filtered-v1.1 |
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anthracite-org/kalo-opus-instruct-22k-no-refusal |
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anthracite-org/nopm_claude_writing_fixed |
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Epiculous/Synthstruct-Gens-v1.1-Filtered-n-Cleaned |
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Epiculous/SynthRP-Gens-v1.1-Filtered-n-Cleaned |
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Training |
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The training was done for 2 epochs. We used 8xH100s GPUs graciously provided by Recursal AI / Featherless AI for the full-parameter fine-tuning of the model. |
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--- |
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## Use with llama.cpp |
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Install llama.cpp through brew (works on Mac and Linux) |
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```bash |
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brew install llama.cpp |
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``` |
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Invoke the llama.cpp server or the CLI. |
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### CLI: |
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```bash |
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llama-cli --hf-repo Triangle104/magnum-v3-9b-customgemma2-Q6_K-GGUF --hf-file magnum-v3-9b-customgemma2-q6_k.gguf -p "The meaning to life and the universe is" |
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``` |
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### Server: |
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```bash |
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llama-server --hf-repo Triangle104/magnum-v3-9b-customgemma2-Q6_K-GGUF --hf-file magnum-v3-9b-customgemma2-q6_k.gguf -c 2048 |
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``` |
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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. |
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Step 1: Clone llama.cpp from GitHub. |
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``` |
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git clone https://github.com/ggerganov/llama.cpp |
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``` |
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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). |
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``` |
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cd llama.cpp && LLAMA_CURL=1 make |
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``` |
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Step 3: Run inference through the main binary. |
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``` |
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./llama-cli --hf-repo Triangle104/magnum-v3-9b-customgemma2-Q6_K-GGUF --hf-file magnum-v3-9b-customgemma2-q6_k.gguf -p "The meaning to life and the universe is" |
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``` |
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or |
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``` |
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./llama-server --hf-repo Triangle104/magnum-v3-9b-customgemma2-Q6_K-GGUF --hf-file magnum-v3-9b-customgemma2-q6_k.gguf -c 2048 |
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``` |
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