Salamander 24B v1 EXL3
Collection
3 items • Updated
How to use dr-housemd/Salamander-24B-v1-exl3-3.50bpw with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-generation", model="dr-housemd/Salamander-24B-v1-exl3-3.50bpw")
messages = [
{"role": "user", "content": "Who are you?"},
]
pipe(messages) # Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM
tokenizer = AutoTokenizer.from_pretrained("dr-housemd/Salamander-24B-v1-exl3-3.50bpw")
model = AutoModelForCausalLM.from_pretrained("dr-housemd/Salamander-24B-v1-exl3-3.50bpw")
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]:]))How to use dr-housemd/Salamander-24B-v1-exl3-3.50bpw with vLLM:
# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "dr-housemd/Salamander-24B-v1-exl3-3.50bpw"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
-H "Content-Type: application/json" \
--data '{
"model": "dr-housemd/Salamander-24B-v1-exl3-3.50bpw",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'docker model run hf.co/dr-housemd/Salamander-24B-v1-exl3-3.50bpw
How to use dr-housemd/Salamander-24B-v1-exl3-3.50bpw with SGLang:
# Install SGLang from pip:
pip install sglang
# Start the SGLang server:
python3 -m sglang.launch_server \
--model-path "dr-housemd/Salamander-24B-v1-exl3-3.50bpw" \
--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": "dr-housemd/Salamander-24B-v1-exl3-3.50bpw",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'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 "dr-housemd/Salamander-24B-v1-exl3-3.50bpw" \
--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": "dr-housemd/Salamander-24B-v1-exl3-3.50bpw",
"messages": [
{
"role": "user",
"content": "What is the capital of France?"
}
]
}'How to use dr-housemd/Salamander-24B-v1-exl3-3.50bpw with Docker Model Runner:
docker model run hf.co/dr-housemd/Salamander-24B-v1-exl3-3.50bpw
Configuration Parsing Warning:In config.json: "quantization_config.bits" must be an integer
3.50bpw exl3 quant. 8 head bits.
Model's Card:
This is Checkpoint 82, a new della merge combining several 2501, 2506, and 2509 models, with fallen mistral 2503 also sprinkled in.
No refusals were observed in the initial tests. The model should not require ablation or jailbreaks.
architecture: MistralForCausalLM
models:
## BASE ##
- model: B:\24B\Darkhn--Magistral-2509-24B-Text-Only
## 2501 ##
- model: B:\24B\!models--ReadyArt--4.2.0-Broken-Tutu-24b
parameters:
weight: 0.1
density: 0.9
epsilon: 0.09
- model: B:\24B\!models--ReadyArt--Broken-Tutu-24B-Transgression-v2.0
parameters:
weight: 0.1
density: 0.9
epsilon: 0.09
- model: B:\24B\PrivateMerge29 # This merge is no longer available on HF
parameters:
weight: 0.1
density: 0.9
epsilon: 0.09
- model: B:\24B\!models--Nabbers1999--MS-24B-Bathory-GRPO
parameters:
weight: 0.1
density: 0.9
epsilon: 0.09
- model: B:\24B\!models--dphn--Dolphin-Mistral-24B-Venice-Edition
parameters:
weight: 0.1
density: 0.9
epsilon: 0.09
- model: B:\24B\!models--TroyDoesAI--BlackSheep-24B
parameters:
weight: 0.1
density: 0.9
epsilon: 0.09
- model: B:\24B\!models--aixonlab--Eurydice-24b-v3.5
parameters:
weight: 0.1
density: 0.9
epsilon: 0.09
- model: B:\24B\!models--Undi95--MistralThinker-v1.1
parameters:
weight: 0.1
density: 0.9
epsilon: 0.09
## 2503 ##
- model: B:\24B\!BeaverAI_Fallen-Mistral-Small-3.1-24B-v1e_textonly
parameters:
weight: 0.2
density: 0.9
epsilon: 0.09
## 2506 ##
- model: B:\24B\!models--zerofata--MS3.2-PaintedFantasy-v2-24B
parameters:
weight: 0.1
weight: 0.09
epsilon: 0.09
- model: B:\24B\!models--TheDrummer--Cydonia-24B-v4.3
parameters:
weight: 0.2
density: 0.9
epsilon: 0.09
- model: B:\24B\!models--TheDrummer--Rivermind-24B-v1
parameters:
weight: 0.1
density: 0.9
epsilon: 0.09
- model: B:\24B\!models--trashpanda-org--MS3.2-24B-Mullein-v2
parameters:
weight: 0.1
density: 0.9
epsilon: 0.09
- model: B:\24B\!models--allura-forge--ms32-final-TEXTONLY
parameters:
weight: 0.1
density: 0.9
epsilon: 0.09
- model: B:\24B\!models--CrucibleLab--M3.2-24B-Loki-V1.3
parameters:
weight: 0.1
density: 0.9
epsilon: 0.09
- model: B:\24B\!models--Darkhn--M3.2-24B-Animus-V7.1
parameters:
weight: 0.1
density: 0.9
epsilon: 0.09
- model: B:\24B\MuXodious--Hearthfire-24B-absolute-heresy
parameters:
weight: 0.1
density: 0.9
epsilon: 0.09
- model: B:\24B\!models--ReadyArt--Dark-Nexus-24B-v2.0
parameters:
weight: 0.1
density: 0.9
epsilon: 0.09
## 2509##
- model: B:\24B\!models--TheDrummer--Precog-24B-v1
parameters:
weight: 0.2
density: 0.9
epsilon: 0.09
- model: B:\24B\!models--TheDrummer--Magidonia-24B-v4.3
parameters:
weight: 0.2
density: 0.9
epsilon: 0.09
- model: B:\24B\llmfan46--MS3.2-PaintedFantasy-v4.1-24B-ultra-uncensored-heretic-v1
parameters:
weight: 0.2
density: 0.9
epsilon: 0.09
- model: B:\24B\!models--zerofata--MS3.2-PaintedFantasy-v3-24B
parameters:
weight: 0.2
density: 0.9
epsilon: 0.09
- model: B:\24B\MuXodious--Tiamat-24B-Magistral-PaperWitch-heresy\textonly
parameters:
weight: 0.2
density: 0.9
epsilon: 0.09
merge_method: della
base_model: B:\24B\Darkhn--Magistral-2509-24B-Text-Only
parameters:
lambda: 1.0
normalize: false
int8_mask: false
rescale: true
tokenizer:
source: union
dtype: float32
out_dtype: bfloat16
name: C82
Base model
Naphula/Salamander-24B-v1