Instructions to use lilmeaty/llama_v5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lilmeaty/llama_v5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="lilmeaty/llama_v5") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("lilmeaty/llama_v5") model = AutoModelForCausalLM.from_pretrained("lilmeaty/llama_v5") 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 lilmeaty/llama_v5 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "lilmeaty/llama_v5" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "lilmeaty/llama_v5", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/lilmeaty/llama_v5
- SGLang
How to use lilmeaty/llama_v5 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 "lilmeaty/llama_v5" \ --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": "lilmeaty/llama_v5", "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 "lilmeaty/llama_v5" \ --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": "lilmeaty/llama_v5", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use lilmeaty/llama_v5 with Docker Model Runner:
docker model run hf.co/lilmeaty/llama_v5
Upload config.json with huggingface_hub
Browse files- config.json +1 -41
config.json
CHANGED
|
@@ -1,41 +1 @@
|
|
| 1 |
-
{
|
| 2 |
-
"_name_or_path": "lilmeaty/llama_v4",
|
| 3 |
-
"architectures": [
|
| 4 |
-
"LlamaForCausalLM"
|
| 5 |
-
],
|
| 6 |
-
"attention_bias": false,
|
| 7 |
-
"attention_dropout": 0.0,
|
| 8 |
-
"bos_token_id": 128000,
|
| 9 |
-
"eos_token_id": [
|
| 10 |
-
128001,
|
| 11 |
-
128008,
|
| 12 |
-
128009
|
| 13 |
-
],
|
| 14 |
-
"head_dim": 64,
|
| 15 |
-
"hidden_act": "silu",
|
| 16 |
-
"hidden_size": 2048,
|
| 17 |
-
"initializer_range": 0.02,
|
| 18 |
-
"intermediate_size": 8192,
|
| 19 |
-
"max_position_embeddings": 131072,
|
| 20 |
-
"mlp_bias": false,
|
| 21 |
-
"model_type": "llama",
|
| 22 |
-
"num_attention_heads": 32,
|
| 23 |
-
"num_hidden_layers": 16,
|
| 24 |
-
"num_key_value_heads": 8,
|
| 25 |
-
"pad_token_id": 128009,
|
| 26 |
-
"pretraining_tp": 1,
|
| 27 |
-
"rms_norm_eps": 1e-05,
|
| 28 |
-
"rope_scaling": {
|
| 29 |
-
"factor": 32.0,
|
| 30 |
-
"high_freq_factor": 4.0,
|
| 31 |
-
"low_freq_factor": 1.0,
|
| 32 |
-
"original_max_position_embeddings": 8192,
|
| 33 |
-
"rope_type": "llama3"
|
| 34 |
-
},
|
| 35 |
-
"rope_theta": 500000.0,
|
| 36 |
-
"tie_word_embeddings": true,
|
| 37 |
-
"torch_dtype": "float32",
|
| 38 |
-
"transformers_version": "4.47.1",
|
| 39 |
-
"use_cache": true,
|
| 40 |
-
"vocab_size": 128256
|
| 41 |
-
}
|
|
|
|
| 1 |
+
{"vocab_size": 128256, "max_position_embeddings": 131072, "hidden_size": 2048, "intermediate_size": 8192, "num_hidden_layers": 16, "num_attention_heads": 32, "num_key_value_heads": 8, "hidden_act": "silu", "initializer_range": 0.02, "rms_norm_eps": 1e-05, "pretraining_tp": 1, "use_cache": true, "rope_theta": 500000.0, "rope_scaling": {"factor": 32.0, "high_freq_factor": 4.0, "low_freq_factor": 1.0, "original_max_position_embeddings": 8192, "rope_type": "llama3"}, "attention_bias": false, "attention_dropout": 0.0, "mlp_bias": false, "head_dim": 64, "return_dict": true, "output_hidden_states": false, "output_attentions": false, "torchscript": false, "torch_dtype": "float32", "use_bfloat16": false, "tf_legacy_loss": false, "pruned_heads": {}, "tie_word_embeddings": true, "chunk_size_feed_forward": 0, "is_encoder_decoder": false, "is_decoder": false, "cross_attention_hidden_size": null, "add_cross_attention": false, "tie_encoder_decoder": false, "max_length": 20, "min_length": 0, "do_sample": false, "early_stopping": false, "num_beams": 1, "num_beam_groups": 1, "diversity_penalty": 0.0, "temperature": 1.0, "top_k": 50, "top_p": 1.0, "typical_p": 1.0, "repetition_penalty": 1.0, "length_penalty": 1.0, "no_repeat_ngram_size": 0, "encoder_no_repeat_ngram_size": 0, "bad_words_ids": null, "num_return_sequences": 1, "output_scores": false, "return_dict_in_generate": false, "forced_bos_token_id": null, "forced_eos_token_id": null, "remove_invalid_values": false, "exponential_decay_length_penalty": null, "suppress_tokens": null, "begin_suppress_tokens": null, "architectures": ["LlamaForCausalLM"], "finetuning_task": null, "id2label": {"0": "LABEL_0", "1": "LABEL_1"}, "label2id": {"LABEL_0": 0, "LABEL_1": 1}, "tokenizer_class": null, "prefix": null, "bos_token_id": 128000, "pad_token_id": 128009, "eos_token_id": [128001, 128008, 128009], "sep_token_id": null, "decoder_start_token_id": null, "task_specific_params": null, "problem_type": null, "_name_or_path": "lilmeaty/llama_v4", "_attn_implementation_autoset": false, "transformers_version": "4.47.1", "model_type": "llama"}
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|