Text Generation
Transformers
TensorBoard
Safetensors
mistral
conversational
text-generation-inference
4-bit precision
bitsandbytes
Instructions to use NobodyExistsOnTheInternet/hermes2-dpo-lora-7b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use NobodyExistsOnTheInternet/hermes2-dpo-lora-7b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="NobodyExistsOnTheInternet/hermes2-dpo-lora-7b") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("NobodyExistsOnTheInternet/hermes2-dpo-lora-7b") model = AutoModelForCausalLM.from_pretrained("NobodyExistsOnTheInternet/hermes2-dpo-lora-7b") messages = [ {"role": "user", "content": "Who are you?"}, ] inputs = tokenizer.apply_chat_template( messages, add_generation_prompt=True, tokenize=True, return_dict=True, return_tensors="pt", ).to(model.device) outputs = model.generate(**inputs, max_new_tokens=40) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use NobodyExistsOnTheInternet/hermes2-dpo-lora-7b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "NobodyExistsOnTheInternet/hermes2-dpo-lora-7b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "NobodyExistsOnTheInternet/hermes2-dpo-lora-7b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/NobodyExistsOnTheInternet/hermes2-dpo-lora-7b
- SGLang
How to use NobodyExistsOnTheInternet/hermes2-dpo-lora-7b with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "NobodyExistsOnTheInternet/hermes2-dpo-lora-7b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "NobodyExistsOnTheInternet/hermes2-dpo-lora-7b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "NobodyExistsOnTheInternet/hermes2-dpo-lora-7b" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "NobodyExistsOnTheInternet/hermes2-dpo-lora-7b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use NobodyExistsOnTheInternet/hermes2-dpo-lora-7b with Docker Model Runner:
docker model run hf.co/NobodyExistsOnTheInternet/hermes2-dpo-lora-7b
Training in progress, step 1000
Browse files- adapter_config.json +35 -0
- adapter_model.safetensors +3 -0
- added_tokens.json +4 -0
- config.json +41 -0
- runs/Feb21_16-11-33_05c27c174db0/events.out.tfevents.1708533268.05c27c174db0.8796.0 +3 -0
- runs/Feb21_16-36-00_05c27c174db0/events.out.tfevents.1708533366.05c27c174db0.8969.0 +3 -0
- runs/Feb21_16-38-18_05c27c174db0/events.out.tfevents.1708533504.05c27c174db0.9101.0 +3 -0
- runs/Feb21_16-47-06_05c27c174db0/events.out.tfevents.1708535394.05c27c174db0.9379.0 +3 -0
- runs/Feb21_17-11-58_05c27c174db0/events.out.tfevents.1708535559.05c27c174db0.9569.0 +3 -0
- runs/Feb21_17-15-53_05c27c174db0/events.out.tfevents.1708535755.05c27c174db0.9725.0 +3 -0
- runs/Feb21_17-19-37_05c27c174db0/events.out.tfevents.1708535979.05c27c174db0.9854.0 +3 -0
- runs/Feb21_17-28-58_05c27c174db0/events.out.tfevents.1708536541.05c27c174db0.9996.0 +3 -0
- runs/Feb21_17-31-52_05c27c174db0/events.out.tfevents.1708536714.05c27c174db0.10108.0 +3 -0
- runs/Feb22_01-40-44_05c27c174db0/events.out.tfevents.1708566046.05c27c174db0.10778.0 +3 -0
- runs/Feb25_03-41-18_05c27c174db0/events.out.tfevents.1708833608.05c27c174db0.11688.0 +3 -0
- runs/Feb25_04-02-43_05c27c174db0/events.out.tfevents.1708833765.05c27c174db0.11905.0 +3 -0
- runs/Feb25_04-04-03_05c27c174db0/events.out.tfevents.1708833844.05c27c174db0.12089.0 +3 -0
- runs/Feb25_04-05-27_05c27c174db0/events.out.tfevents.1708833930.05c27c174db0.12300.0 +3 -0
- runs/Feb25_04-08-40_05c27c174db0/events.out.tfevents.1708834124.05c27c174db0.12680.0 +3 -0
- runs/Feb25_04-10-03_05c27c174db0/events.out.tfevents.1708834206.05c27c174db0.12863.0 +3 -0
- runs/Feb25_04-11-29_05c27c174db0/events.out.tfevents.1708834292.05c27c174db0.13046.0 +3 -0
- runs/Feb25_04-14-13_05c27c174db0/events.out.tfevents.1708834457.05c27c174db0.13230.0 +3 -0
- runs/Feb25_04-15-38_05c27c174db0/events.out.tfevents.1708834542.05c27c174db0.13414.0 +3 -0
- runs/Feb25_04-17-30_05c27c174db0/events.out.tfevents.1708834651.05c27c174db0.13654.0 +3 -0
- runs/Feb25_04-51-25_05c27c174db0/events.out.tfevents.1708836688.05c27c174db0.69.0 +3 -0
- special_tokens_map.json +30 -0
- tokenizer.json +0 -0
- tokenizer.model +3 -0
- tokenizer_config.json +62 -0
- training_args.bin +3 -0
adapter_config.json
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{
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"alpha_pattern": {},
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"auto_mapping": null,
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"base_model_name_or_path": "NousResearch/Nous-Hermes-2-Mistral-7B-DPO",
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"bias": "none",
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"fan_in_fan_out": null,
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"inference_mode": true,
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"init_lora_weights": true,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 64,
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"lora_dropout": 0.05,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": [
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"embed_tokens",
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"lm_head"
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],
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"peft_type": "LORA",
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"r": 32,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"k_proj",
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"q_proj",
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"down_proj",
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"gate_proj",
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"up_proj",
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"v_proj",
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"o_proj"
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],
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"task_type": "CAUSAL_LM",
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"use_rslora": false
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}
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adapter_model.safetensors
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added_tokens.json
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{
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"<|im_end|>": 32000,
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config.json
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{
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"_name_or_path": "NousResearch/Nous-Hermes-2-Mistral-7B-DPO",
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"architectures": [
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"MistralForCausalLM"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 1,
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"eos_token_id": 32000,
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"hidden_act": "silu",
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"intermediate_size": 14336,
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"max_position_embeddings": 32768,
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"model_type": "mistral",
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"num_attention_heads": 32,
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"num_hidden_layers": 32,
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"num_key_value_heads": 8,
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"quantization_config": {
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"_load_in_4bit": true,
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"_load_in_8bit": false,
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"bnb_4bit_compute_dtype": "float16",
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"bnb_4bit_quant_type": "nf4",
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"bnb_4bit_use_double_quant": true,
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"llm_int8_enable_fp32_cpu_offload": false,
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"llm_int8_skip_modules": null,
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"load_in_4bit": true,
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"load_in_8bit": false,
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"quant_method": "bitsandbytes"
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},
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"rms_norm_eps": 1e-05,
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"rope_scaling": null,
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"rope_theta": 10000.0,
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"sliding_window": 4096,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.38.0",
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"use_cache": false,
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"vocab_size": 32002
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}
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special_tokens_map.json
ADDED
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"single_word": false
|
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}
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| 30 |
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}
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tokenizer.json
ADDED
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tokenizer.model
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:dadfd56d766715c61d2ef780a525ab43b8e6da4de6865bda3d95fdef5e134055
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size 493443
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tokenizer_config.json
ADDED
|
@@ -0,0 +1,62 @@
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|
| 1 |
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{
|
| 2 |
+
"add_bos_token": true,
|
| 3 |
+
"add_eos_token": false,
|
| 4 |
+
"add_prefix_space": true,
|
| 5 |
+
"added_tokens_decoder": {
|
| 6 |
+
"0": {
|
| 7 |
+
"content": "<unk>",
|
| 8 |
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"lstrip": false,
|
| 9 |
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"normalized": false,
|
| 10 |
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"rstrip": false,
|
| 11 |
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"single_word": false,
|
| 12 |
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"special": true
|
| 13 |
+
},
|
| 14 |
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"1": {
|
| 15 |
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"content": "<s>",
|
| 16 |
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|
| 17 |
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|
| 18 |
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|
| 19 |
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"single_word": false,
|
| 20 |
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"special": true
|
| 21 |
+
},
|
| 22 |
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"2": {
|
| 23 |
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"content": "</s>",
|
| 24 |
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"lstrip": false,
|
| 25 |
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"normalized": false,
|
| 26 |
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"rstrip": false,
|
| 27 |
+
"single_word": false,
|
| 28 |
+
"special": true
|
| 29 |
+
},
|
| 30 |
+
"32000": {
|
| 31 |
+
"content": "<|im_end|>",
|
| 32 |
+
"lstrip": false,
|
| 33 |
+
"normalized": false,
|
| 34 |
+
"rstrip": false,
|
| 35 |
+
"single_word": false,
|
| 36 |
+
"special": true
|
| 37 |
+
},
|
| 38 |
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"32001": {
|
| 39 |
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"content": "<|im_start|>",
|
| 40 |
+
"lstrip": false,
|
| 41 |
+
"normalized": false,
|
| 42 |
+
"rstrip": false,
|
| 43 |
+
"single_word": false,
|
| 44 |
+
"special": true
|
| 45 |
+
}
|
| 46 |
+
},
|
| 47 |
+
"additional_special_tokens": [],
|
| 48 |
+
"bos_token": "<s>",
|
| 49 |
+
"chat_template": "{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% else %}{% set loop_messages = messages %}{% set system_message = 'Generate a preferable answer.' %}{% endif %}{% if not add_generation_prompt is defined %}{% set add_generation_prompt = false %}{% endif %}{% for message in loop_messages %}{% if loop.index0 == 0 %}{{'<|im_start|>system\n' + system_message + '<|im_end|>\n'}}{% endif %}{{'<|im_start|>' + message['role'] + '\n' + message['content'] + '<|im_end|>' + '\n'}}{% endfor %}{% if add_generation_prompt %}{{ '<|im_start|>assistant\n' }}{% endif %}",
|
| 50 |
+
"clean_up_tokenization_spaces": false,
|
| 51 |
+
"eos_token": "<|im_end|>",
|
| 52 |
+
"legacy": true,
|
| 53 |
+
"model_max_length": 1000000000000000019884624838656,
|
| 54 |
+
"pad_token": "</s>",
|
| 55 |
+
"sp_model_kwargs": {},
|
| 56 |
+
"spaces_between_special_tokens": false,
|
| 57 |
+
"tokenizer_class": "LlamaTokenizer",
|
| 58 |
+
"trust_remote_code": false,
|
| 59 |
+
"unk_token": "<unk>",
|
| 60 |
+
"use_default_system_prompt": true,
|
| 61 |
+
"use_fast": true
|
| 62 |
+
}
|
training_args.bin
ADDED
|
@@ -0,0 +1,3 @@
|
|
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|
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|
|
|
|
|
|
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|
| 1 |
+
version https://git-lfs.github.com/spec/v1
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| 2 |
+
oid sha256:7f4504e1370becb80d1d6feb0f2ec638b6dc2e19b049b813e8eb5337a7649e82
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| 3 |
+
size 5048
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