Text Generation
Transformers
Safetensors
English
qwen2
qwen2.5
sakthai
house-of-sak
tool-calling
function-calling
agent
instruct
finetuned
sft
merged
conversational
assistant
cpu-inference
rsLoRA
benchmark
Eval Results
llama-cpp
Eval Results (legacy)
text-generation-inference
Instructions to use Nanthasit/sakthai-plus-1.5b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use Nanthasit/sakthai-plus-1.5b with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Nanthasit/sakthai-plus-1.5b") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer = AutoTokenizer.from_pretrained("Nanthasit/sakthai-plus-1.5b") model = AutoModelForCausalLM.from_pretrained("Nanthasit/sakthai-plus-1.5b", device_map="auto") 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=256) print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:])) - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use Nanthasit/sakthai-plus-1.5b with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "Nanthasit/sakthai-plus-1.5b" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "Nanthasit/sakthai-plus-1.5b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }'Use Docker
docker model run hf.co/Nanthasit/sakthai-plus-1.5b
- SGLang
How to use Nanthasit/sakthai-plus-1.5b 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 "Nanthasit/sakthai-plus-1.5b" \ --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": "Nanthasit/sakthai-plus-1.5b", "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 "Nanthasit/sakthai-plus-1.5b" \ --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": "Nanthasit/sakthai-plus-1.5b", "messages": [ { "role": "user", "content": "What is the capital of France?" } ] }' - Docker Model Runner
How to use Nanthasit/sakthai-plus-1.5b with Docker Model Runner:
docker model run hf.co/Nanthasit/sakthai-plus-1.5b
Upload Qwen2ForCausalLM
Browse files- config.json +7 -4
- generation_config.json +1 -1
- model.safetensors +2 -2
config.json
CHANGED
|
@@ -4,7 +4,7 @@
|
|
| 4 |
],
|
| 5 |
"attention_dropout": 0.0,
|
| 6 |
"bos_token_id": 151643,
|
| 7 |
-
"dtype": "
|
| 8 |
"eos_token_id": 151645,
|
| 9 |
"hidden_act": "silu",
|
| 10 |
"hidden_size": 1536,
|
|
@@ -46,12 +46,15 @@
|
|
| 46 |
"num_attention_heads": 12,
|
| 47 |
"num_hidden_layers": 28,
|
| 48 |
"num_key_value_heads": 2,
|
|
|
|
| 49 |
"rms_norm_eps": 1e-06,
|
| 50 |
-
"
|
| 51 |
-
|
|
|
|
|
|
|
| 52 |
"sliding_window": null,
|
| 53 |
"tie_word_embeddings": true,
|
| 54 |
-
"transformers_version": "
|
| 55 |
"use_cache": true,
|
| 56 |
"use_sliding_window": false,
|
| 57 |
"vocab_size": 151936
|
|
|
|
| 4 |
],
|
| 5 |
"attention_dropout": 0.0,
|
| 6 |
"bos_token_id": 151643,
|
| 7 |
+
"dtype": "bfloat16",
|
| 8 |
"eos_token_id": 151645,
|
| 9 |
"hidden_act": "silu",
|
| 10 |
"hidden_size": 1536,
|
|
|
|
| 46 |
"num_attention_heads": 12,
|
| 47 |
"num_hidden_layers": 28,
|
| 48 |
"num_key_value_heads": 2,
|
| 49 |
+
"pad_token_id": null,
|
| 50 |
"rms_norm_eps": 1e-06,
|
| 51 |
+
"rope_parameters": {
|
| 52 |
+
"rope_theta": 1000000.0,
|
| 53 |
+
"rope_type": "default"
|
| 54 |
+
},
|
| 55 |
"sliding_window": null,
|
| 56 |
"tie_word_embeddings": true,
|
| 57 |
+
"transformers_version": "5.14.1",
|
| 58 |
"use_cache": true,
|
| 59 |
"use_sliding_window": false,
|
| 60 |
"vocab_size": 151936
|
generation_config.json
CHANGED
|
@@ -10,5 +10,5 @@
|
|
| 10 |
"temperature": 0.7,
|
| 11 |
"top_k": 20,
|
| 12 |
"top_p": 0.8,
|
| 13 |
-
"transformers_version": "
|
| 14 |
}
|
|
|
|
| 10 |
"temperature": 0.7,
|
| 11 |
"top_k": 20,
|
| 12 |
"top_p": 0.8,
|
| 13 |
+
"transformers_version": "5.14.1"
|
| 14 |
}
|
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
-
size
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:99a5220e5867caed7b5fa5c2db52ca936c15c352da701656dea1ae66b90854ac
|
| 3 |
+
size 3087467144
|