Instructions to use Tesleum/0xCoder with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use Tesleum/0xCoder with Transformers:

# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-generation", model="Tesleum/0xCoder")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("Tesleum/0xCoder")
model = AutoModelForCausalLM.from_pretrained("Tesleum/0xCoder", 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=40)
print(tokenizer.decode(outputs[0][inputs["input_ids"].shape[-1]:]))

Notebooks
Google Colab
Kaggle
Local Apps Settings

vLLM

How to use Tesleum/0xCoder with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "Tesleum/0xCoder"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "Tesleum/0xCoder",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/Tesleum/0xCoder

SGLang

How to use Tesleum/0xCoder 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 "Tesleum/0xCoder" \
    --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": "Tesleum/0xCoder",
		"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 "Tesleum/0xCoder" \
        --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": "Tesleum/0xCoder",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Docker Model Runner
How to use Tesleum/0xCoder with Docker Model Runner:
```
docker model run hf.co/Tesleum/0xCoder
```

stevelionheart commited on 12 days ago

Commit

a6fab4b

verified ·

1 Parent(s): a9e276c

Update chat_template.jinja

Browse files

Files changed (1) hide show

chat_template.jinja +4 -4

chat_template.jinja CHANGED Viewed

@@ -1,4 +1,4 @@
-{# Copyright 2025-present Unsloth. Apache 2.0 License. Unsloth chat template fixes. Edited from ggml-org & OpenAI #}
 {#-
   In addition to the normal inputs of `messages` and `tools`, this template also accepts the
   following kwargs:
@@ -195,11 +195,11 @@
 {#- System Message Construction ============================================ #}
 {%- macro build_system_message() -%}
     {%- if model_identity is not defined %}
-        {{- "You are ChatGPT, a large language model trained by OpenAI.\n" -}}
     {%- else %}
         {{- model_identity }}
     {%- endif %}
-    {{- "Knowledge cutoff: 2024-06\n" }}
     {{- "Current date: " + strftime_now("%Y-%m-%d") + "\n\n" }}
     {%- if reasoning_effort is not defined %}
         {%- set reasoning_effort = "medium" %}
@@ -312,4 +312,4 @@
 {%- if add_generation_prompt -%}
 <|start|>assistant
 {%- endif -%}
-{# Copyright 2025-present Unsloth. Apache 2.0 License. Unsloth chat template fixes. Edited from ggml-org & OpenAI #}

+{# Copyright 2026-present Tesleum. Edited from ggml-org & Antropic #}
 {#-
   In addition to the normal inputs of `messages` and `tools`, this template also accepts the
   following kwargs:
 {#- System Message Construction ============================================ #}
 {%- macro build_system_message() -%}
     {%- if model_identity is not defined %}
+        {{- "You are Claude Fable 5, a large language model trained by Antropic.\n" -}}
     {%- else %}
         {{- model_identity }}
     {%- endif %}
+    {{- "Knowledge cutoff: 2026-07\n" }}
     {{- "Current date: " + strftime_now("%Y-%m-%d") + "\n\n" }}
     {%- if reasoning_effort is not defined %}
         {%- set reasoning_effort = "medium" %}
 {%- if add_generation_prompt -%}
 <|start|>assistant
 {%- endif -%}
+{# Copyright 2026-present Tesleum. Edited from ggml-org & Antropic #}