Text Generation
MLX
Safetensors
GGUF
Rust
qwen3_5_text
4b
agentic-coding
android
apple-silicon
attested
bash
c
chain-of-custody
chinese
code
code-completion
code-generation
code-infill
coder
coding
consumer-gpu
cpp
cryptographically-verified
css
delta-forge
edge-inference
embedded
english
forge-alloy
function-calling
ggml
go
html
iphone
java
javascript
kotlin
llama-cpp
lm-studio
local-inference
macbook
mobile
multilingual
ollama
on-device
php
programming
python
q4-k-m
quantized
qwen
qwen3
qwen3.5
raspberry-pi
reproducible
ruby
software-engineering
sql
swift
typescript
Instructions to use continuum-ai/qwen3.5-4b-code-forged with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use continuum-ai/qwen3.5-4b-code-forged with MLX:
# Make sure mlx-lm is installed # pip install --upgrade mlx-lm # if on a CUDA device, also pip install mlx[cuda] # Generate text with mlx-lm from mlx_lm import load, generate model, tokenizer = load("continuum-ai/qwen3.5-4b-code-forged") prompt = "Once upon a time in" text = generate(model, tokenizer, prompt=prompt, verbose=True) - Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
- MLX LM
How to use continuum-ai/qwen3.5-4b-code-forged with MLX LM:
Generate or start a chat session
# Install MLX LM uv tool install mlx-lm # Generate some text mlx_lm.generate --model "continuum-ai/qwen3.5-4b-code-forged" --prompt "Once upon a time"
Upload config.json with huggingface_hub
Browse files- config.json +2 -2
config.json
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"mamba_ssm_dtype": "float32",
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"max_position_embeddings": 262144,
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"mlp_only_layers": [],
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"model_type": "
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"mtp_num_hidden_layers": 1,
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"mtp_use_dedicated_embeddings": false,
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"num_attention_heads": 16,
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"transformers_version": "5.3.0",
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"use_cache": true,
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"vocab_size": 248320
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}
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"mamba_ssm_dtype": "float32",
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"max_position_embeddings": 262144,
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"mlp_only_layers": [],
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"model_type": "qwen3_5",
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"mtp_num_hidden_layers": 1,
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"mtp_use_dedicated_embeddings": false,
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"num_attention_heads": 16,
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"transformers_version": "5.3.0",
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"use_cache": true,
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"vocab_size": 248320
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}
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