Instructions to use AlSamCur123/MistralContinuedFine with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Libraries

How to use AlSamCur123/MistralContinuedFine with Transformers:

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

pipe = pipeline("text-generation", model="AlSamCur123/MistralContinuedFine")
messages = [
    {"role": "user", "content": "Who are you?"},
]
pipe(messages)

# Load model directly
from transformers import AutoTokenizer, AutoModelForCausalLM

tokenizer = AutoTokenizer.from_pretrained("AlSamCur123/MistralContinuedFine")
model = AutoModelForCausalLM.from_pretrained("AlSamCur123/MistralContinuedFine")
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

vLLM

How to use AlSamCur123/MistralContinuedFine with vLLM:

Install from pip and serve model

# Install vLLM from pip:
pip install vllm
# Start the vLLM server:
vllm serve "AlSamCur123/MistralContinuedFine"
# Call the server using curl (OpenAI-compatible API):
curl -X POST "http://localhost:8000/v1/chat/completions" \
	-H "Content-Type: application/json" \
	--data '{
		"model": "AlSamCur123/MistralContinuedFine",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Use Docker

docker model run hf.co/AlSamCur123/MistralContinuedFine

SGLang

How to use AlSamCur123/MistralContinuedFine 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 "AlSamCur123/MistralContinuedFine" \
    --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": "AlSamCur123/MistralContinuedFine",
		"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 "AlSamCur123/MistralContinuedFine" \
        --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": "AlSamCur123/MistralContinuedFine",
		"messages": [
			{
				"role": "user",
				"content": "What is the capital of France?"
			}
		]
	}'

Unsloth Studio

How to use AlSamCur123/MistralContinuedFine with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for AlSamCur123/MistralContinuedFine to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for AlSamCur123/MistralContinuedFine to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for AlSamCur123/MistralContinuedFine to start chatting

Load model with FastModel

pip install unsloth
from unsloth import FastModel
model, tokenizer = FastModel.from_pretrained(
    model_name="AlSamCur123/MistralContinuedFine",
    max_seq_length=2048,
)

Docker Model Runner
How to use AlSamCur123/MistralContinuedFine with Docker Model Runner:
```
docker model run hf.co/AlSamCur123/MistralContinuedFine
```

AlSamCur123 commited on Nov 5, 2024

Commit

a34424f

verified ·

1 Parent(s): 03e3267

Trained with Unsloth

Browse files

Files changed (4) hide show

config.json +1 -1
model-00001-of-00003.safetensors +1 -1
model-00002-of-00003.safetensors +1 -1
model-00003-of-00003.safetensors +1 -1

config.json CHANGED Viewed

@@ -1,5 +1,5 @@
 {
-  "_name_or_path": "AlSamCur123/MistralContinuedFine",
   "architectures": [
     "MistralForCausalLM"
   ],

 {
+  "_name_or_path": "unsloth/mistral-7b-instruct-v0.3-bnb-4bit",
   "architectures": [
     "MistralForCausalLM"
   ],

model-00001-of-00003.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:0a70b5bf5f35d12686e3cff0d71292eb927265b0cc46e07810362a5d5d63e855
 size 4949453696

 version https://git-lfs.github.com/spec/v1
+oid sha256:ae13c25a94a134b938ac3ddbc8d109eb388018ae1e2efcc0dae1c2958ad5b862
 size 4949453696

model-00002-of-00003.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:88fada1eca22b94bfbd6187026df31539f88b4134af32cd98a67d9e6499524e5
 size 4999819232

 version https://git-lfs.github.com/spec/v1
+oid sha256:dce52a9b2572a13cdef4f019edc2255ee3b2b028559b1402923f0c6454b7bf38
 size 4999819232

model-00003-of-00003.safetensors CHANGED Viewed

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:60b735f3f6cdaec214e33bc9efd3d7bdc831bc79156e9b5fceeefb8e9192e34e
 size 4546807712

 version https://git-lfs.github.com/spec/v1
+oid sha256:c7c248d5d13f6f1a35941720549426a19168590db6af2ecfd037b412de107fc5
 size 4546807712